Are your clinical AI pilots still waiting on patient data spread across separate systems? That is one of the gates between a pilot and a live clinical workflow. Security review, scale, and governance are the others.

Tomorrow, @Microsoft and @Simform experts will work through our online session. If healthcare AI agents are on your 2027 roadmap, this is the session to join before those priorities are locked in.

- Building the Intelligent Healthcare Enterprise, covering FHIR, Microsoft Fabric, Azure AI Foundry, healthcare agents, and responsible AI

- Live demos of Simform’s MedSweep, MedNoteDX, and Patient360 accelerators

Hear from Tanguy Carrere (Sales Leader, Microsoft), Ritesh Shah (Field CTO, Simform), and Puneet Jeyasingh (HealthcareAI Architect, Microsoft).

📅 November 5, 2026
⏱️ 9:30 to 11:30 AM ET
📍 Online
🔗 Register now: simform.com/event/virtual-…

#MicrosoftPartner #MSPartner

We go live tomorrow at 9 AM PT.

In one hour, @Simform and @Microsoft walk through activating a governed patient data estate in #MicrosoftFabric through #MicrosoftFoundry, and the six decisions that turn it into clinical intelligence.

- Which clinical AI use case to start with
- upport before it ships
- Grounding outputs in trusted enterprise data with Foundry
- Build or buy for the first deployment
- Where human review belongs
- How to sequence the use cases that follow

If a governed data estate is still waiting on its first clinical #AIworkflow, join us live.

Register: simform.com/webinar/unifie…

📅 Tomorrow, October 15 | 9–10 AM PT · 12–1 PM ET

🗣 Speakers:
Ritesh Shah, Field CTO, Simform
Chase Dixon, Cloud & AI Specialist, Microsoft

#DigitalHealth #MSPartner

Simform has earned the Microsoft Azure Virtual Desktop specialization.

This milestone validates our expertise in deploying, optimizing, and securing virtual desktop infrastructure on Azure. A desktop migration that leaves identity, networking, and security unchanged carries the the cloud, so we align them under one modernization program.

What does this mean for your business?

- Scale your virtual workspace as workforce needs change, with host pools, identity, and networking designed using the Azure Well-Architected Framework.

- Extend your Azure security controls into the desktop environment through least-privilege access and Microsoft Defender for Endpoint.

- Manage cost and reliability after go-live with our 24x7 managed services and SimOps, our proprietary platform that tracks Azure consumption.

As an Azure Expert MSP with ten @Microsoft specializations, we co-engineer virtual desktop modernization as part of your wider Azure environment.

Read the full story here: simform.com/blog/azure-vir…

An AI policy that sits in a document does very little when an agent finds a way around its rules.

In the next #ECAFVoices episode, host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, sits down with Adrian S., Chief Information Security Officer (CISO) at a leading #healthcare ompany, to talk about guardrails that keep getting bypassed and the gap between writing governance and enforcing it.

Watch the trailer for a first look! Full episode coming soon.

Thank you to everyone who visited us at Booth 17 during FabCon Europe 2026, and to everyone who joined the FabCon Pre-Game on Wednesday evening.

Across four days in Barcelona, one theme came up again and again. Teams want a Fabric platform they can rely on in production, and governance as the thing that makes that possible rather than paperwork that slows them down.

At the booth, we compared notes on:

- Phased migrations planned around production schedules

- TrueMorph in action: AI-powered data warehouse modernization

- Making Fabric spend legible with capacity governance and FinOps

- DataOps discipline that turns Fabric pilots into production platforms

Thank you for spending time with us. We look forward to continuing these conversations.

@Simform has earned the Microsoft Solutions Partner designation for AI Business Solutions, completing our coverage across all Microsoft AI Cloud solution areas.

We are now one of fewer than 50 companies globally to hold Azure Expert MSP recognition alongside all three Solutions loud & AI Platforms, AI Business Solutions, and Security.

This milestone strengthens our ability to help enterprises move beyond isolated AI initiatives by connecting strategy, platform, governance, and execution across the Microsoft ecosystem.

Through our Agentic Operating Model and Microsoft-aligned AI platform strategy, we help organizations redesign workflows, establish governance, and scale AI toward production outcomes.

Read the full breakdown: simform.com/blog/simform-c…

Thank you to our @Microsoft teams and our customers who continue to put these capabilities to work.

#MSPartner #MicrosoftPartner

Healthcare can move data between systems and still lose the context that matters.

Murali Vemulapalli uses a prescription refill to show where the friction appears:

- The request can cross the provider, pharmacy, payer, & PBM
- Eligibility may be checked repeatedly across those syston problem can turn a routine workflow into a delay

Interoperability is not only about moving records. Context has to survive the journey.

Muralidhar Vemulapalli, Chief Enterprise Architect / Acting CTO at Leading Managed Healthcare Industry, explains why context remains a hard Health Tech interoperability problem.

Watch Muralidhar Vemulapalli and Rameshwar Balanagu's full conversation now: simform.com/podcast/enterp…

Spend $5,000,000 to automate work that already costs $9 an hour? Or just hire more people at $9 an hour.

That objection is where most enterprise AI business cases quietly die. Leaders debate models and budgets while the real constraint sits somewhere else entirely: nobody can and the use cases are being picked by guesswork.

In the third episode of ECAF Voices, Brandon Micci, Head of AI Strategy & Business Transformation at J.P. Morgan, joins host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, for a conversation that names the parts most teams would rather not audit:

- Why the productivity everyone planned for has not arrived.

- What a first AI use case actually costs in months before it clears governance.

- Where AI fails when it is dropped into a platform people already avoid.

- And why the work being automated first is the work that produces your next leaders.

Here's the teaser. The full episode drops soon.

#ECAFVoices

AI risk changes when one failure pattern can operate at enterprise scale.

Murali Vemulapalli explains why autonomy, governance and control have to evolve together.

Watch the complete ECAF Voices conversation in the full episode: simform.com/podcast/enterp…

#EnterpriseAI #AIGovernance

When a human makes a bad decision, it does not go viral. When AI makes one, it does. Muralidhar Vemulapalli argues the governance to meet that standard does not exist yet.

Episode 2 of ECAF Voices, our Enterprise Cloud and AI Forum series, is now live.

Rameshwar Balanagu, O Club, sits down with Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at a leading managed healthcare company, on why the risk in scaling AI is the million instances that repeat a bad decision, not the single incident.

Murali brings 25 years of health tech across large payers. He walks through what he calls Layer 6, his governance and observability layer, and separates human in the loop, human on the loop, and high agency. His warning: leaders who treat AI governance as somebody else's job carry the implications personally.

The conversation stays on how these decisions get made, not on tooling.

Full episode: simform.com/podcast/enterp…

Where does your organization sit today: human in the loop, human on the loop, or high agency in narrow workflows?

When a human makes a bad decision, it doesn't go viral. When AI makes one, it does.

That asymmetry is where most enterprise AI conversations fall apart. Leaders debate model accuracy while the real exposure sits somewhere else entirely: governance that hasn't caught up to the yed at.

In the next episode of ECAF Voices, Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at a Leading Managed Healthcare Industry, joins host Rameshwar Balanagu, Co-Founder of Dallas CTO Club, for a conversation that gets uncomfortable in the right ways:

- Why the scale of AI, not the individual incident, is what should concern you.

- What happens when regulation moves slower than the technology it's meant to govern.

- Where the margin of error goes to zero, and what that forces you to rethink.

- And why AI governance is not somebody else's job. It's yours.

Here’s the teaser. The full episode drops soon.

#ECAFVoices

The pilot worked. That is usually where the real problem starts.

Episode 1 of ECAF Voices, our Enterprise Cloud and AI Forum series, is now live.

Rameshwar Balanagu, Co-Founder at Dallas CTO Club, is joined by Shuchi Agrawal, Head of AI Execution at SMBC Group, for a execution gap: the distance between a demo that impresses a steering committee and a system a regulated business can actually run.

Shuchi has spent 25 years building AI and data systems across aviation, global banking, and financial services. She maps the four specific points where enterprise AI programs break before they ship, and makes one point most teams learn the expensive way: token economics belongs in your architecture decisions, not in a budget review after the fact.

The conversation stays on how those decisions actually get made rather than on tooling.

The full episode is on the ECAF Voices page: simform.com/podcast/enterp…

Where is the execution gap widest in your organization right now: the data foundation, the integration work, or adoption?

Cloud and AI strategies are everywhere. Production systems that live up to them are not.

That distance is the execution gap.

It shows up between a boardroom decision and the platforms, data, governance, and operating models needed to make that decision real.

ECAF Voices, the Enterprise Cloud & AI Forum, brings that gap into the open through candid conversations with leaders responsible for closing it.

Hosted by Rameshwar Balanagu, Co-Founder of Dallas CTO Club, the upcoming series features Shuchi Agrawal, Head of AI Execution at SMBC Group; Muralidhar Vemulapalli, Chief Enterprise Architect and Acting CTO at Arkansas Blue Cross and Blue Shield; and Brandon Micci, Head of AI Strategy & Business Transformation at J.P. Morgan, and many more guests.

The teaser offers a first glimpse of conversations grounded in real decisions: what it takes to move AI beyond experimentation, modernize the platforms underneath it, and build governance into execution.

ECAF Voices is coming soon.

Where does the execution gap show up most clearly in your organization: platform, data, governance, or operating model?

Simform's TrueMorph, AI-native data modernization solution, has achieved Microsoft Azure IP Co-sell eligible status.

This status lets Microsoft's own sellers identify TrueMorph for qualified co-sell opportunities, and gives enterprises a Marketplace-based procurement path for zation, with purchases applying toward existing Azure Consumption Commitments.

Here is what this status is built on:

- AI-powered data profiling, transformation, and quality checks, with built-in migration paths for legacy stacks like SSRS, SSIS, SSAS, OBIEE, OBIP, and Informatica Power Center

- Governance embedded at every layer, backed by Azure Key Vault, Microsoft Entra ID, Purview, Unity Catalog, and Azure Monitor

We recently used TrueMorph to help a multi-region retail and vending operator unify 400 to 500 GB of scattered operational data on Microsoft Fabric, cutting stockouts by 30% and speeding up deliveries by 20%.

"With Azure IP Co-sell status, our TrueMorph solution is validated to work in the Fabric ecosystem, and it lets @Microsoft and @Simform field teams go to market together, which is what actually helps customers move faster," shared Juan Llovet de Casso, Cloud Solution Architect at Microsoft.

Thank you to everyone at Simform who built and delivered this.

#MSPartner #MicrosoftPartner

Microsoft’s $2.5B Frontier Company investment points to where enterprise AI is heading next.

Not more pilots. Not more model shopping. Engineering.

@Microsoft is embedding 6,000 industry and engineering experts with customers to co-design, deploy, and continuously improve AI le outcomes.

The important shift is the operating model behind it: Intelligence + Trust.

Enterprise intelligence lives in proprietary data, workflows, expertise, and decision logic.

And the trust comes from the architecture around it, comprising governed data access, context engineering, evals, observability, model routing, FinOps, human review, and IP protection.

That is the same direction @Simform has been engineering toward.

We have been building reusable foundations for this phase: 𝐓𝐫𝐮𝐞𝐌𝐨𝐫𝐩𝐡 to turn fragmented data into secure, AI-ready foundations; 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐌𝐞𝐬𝐡 to design governed agentic systems; and 𝐏𝐞𝐱𝐀𝐈 and 𝐂𝐨𝐝𝐞𝐓𝐨𝐨𝐥𝐬 to bring AI-native discipline across delivery, review, and modernization.

The next phase of enterprise AI will not be won by the team with the most agents.

It will be won by the team that can make enterprise intelligence compound safely, measurably, and inside production systems.

That has always been an engineering problem first.

#mspartner #microsoftpartner

As @Microsoft reduces the infrastructure friction for deploying AI agents, the architecture decisions that determine whether these agents operate reliably in production matter more, not less.

At Build 2026, Windows 365 for Agents reached general availability within Agent 365, ged Cloud PCs for agents working across modern apps, legacy systems, and UI-driven workflows.

Microsoft Foundry also expanded its runtime, evaluation, and governance capabilities, while Microsoft Execution Containers remained in early preview.

The platform can provide execution, containment, and controls. It cannot decide who owns a cross-system process.

An agent that works in a pilot can still fail in production if no one defines the accountable process owner, approval thresholds, or recovery path when a workflow crosses a CRM, ERP, and claims system.

For high-consequence workflows, the more defensible pattern is bounded autonomy. Authority should expand only when actions are observable, attributable, recoverable, and proven through evaluation.

The boundary should follow the consequence and reversibility of the action, not the capability of the model.

@Simform uses 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐌𝐞𝐬𝐡 within agentic AI engagements to implement the orchestration, access, observability, and governance controls behind those decisions.

Skip this work, and the risks surface later as audit gaps, unreliable approval paths, and substantial rework before workflows can scale.

#microsoftpartner #mspartner

Most enterprises do not have a data platform problem. They have a fragmentation problem.

Here’s exactly how #MicrosoftFabric is designed to solve it:

- Fabric consolidates services that used to run separately, like Data Factory, data science workloads, and Power BI, into one ngle billing architecture and shared compute

- OneLake sits at the centre as a unified storage layer built on the Delta open table format, enabling lakehouse, data warehouse, and ML use cases from the same foundation

- Native governance through Microsoft Purview and real-time intelligence through Event Hub come built in, not bolted on

One platform. One storage layer. One place to govern it all.

Anamika Shaw, Sr. Data Architect at @Simform, Rachael Villalaz, Cloud & AI Specialist at @Microsoft, and Matthew Wendel, Principal Solutions Consultant at @Simform, break down how manufacturing and retail organisations can modernise their data estates using Microsoft Fabric.

Watch the full session here: simform.com/lp/webinar-mod…

#MSPartner #MIcrosoftPartner

Clean data does not automatically make enterprise AI reliable.

@ISG_News reports that more than half of organizations still struggle with legacy data residing in old applications, compounding the overall data silo issue and creating further roadblocks to value from AI.

But lone does not resolve every data problem.

Consider "active customer." If three business units define it differently, an agent querying enterprise data has no authoritative meaning to reason against. It can retrieve more records and still return conflicting answers that require manual verification.

That is why semantic governance must be part of data-platform modernization, alongside data quality and ETL improvements.

On #MicrosoftFabric, Power BI semantic models can expose governed measures, relationships, and business terminology within a domain. Fabric IQ ontology can extend those definitions across domains, although it remains in preview and currently requires external change-management controls.

The practical sequence is smaller than an enterprise-wide ontology program:

- Start with one agent use case.
- Identify the entities it must interpret.
- Assign authoritative definitions and owners.
- Then test the agent against verified business questions before expanding.

Without a governed business meaning, better data access can widen an agent’s reach without improving its reliability.

The hidden cost shows up in continued human verification.

#EnterpriseAI adoption doesn't stall because teams lack ambition. It stalls because the three layers that matter most are never designed to work as one.

The data layer. The agent layer. The governance layer.

When they're built in isolation, you get pilots that impress and p.

When they're built together, the picture looks different.

Organizations that connect #MicrosoftFabric as their data foundation with #CopilotStudio and #AIFoundry for agent creation and orchestration report measurable outcomes once they move beyond the POC stage.

- Time from data ingestion to actionable insight: reduced from days to hours in structured deployments

- AI program deployment cycles: compressed by 30–40% when governance is designed in from the start, not retrofitted

- Duplicate agent logic and redundant retrieval paths: cut significantly when a unified semantic layer is in place

The session on July 9 is built around this exact architecture: how Fabric handles the data, how Copilot Studio and AI Foundry handle the agents, and how governance keeps the whole system production-ready.

Not theory. A practical walkthrough with real-world architecture decisions.

@Simform and @Microsoft experts will cover how to identify the right use cases, where readiness gaps typically appear, and how to build a roadmap that holds up.

📅 July 9, 2026 | 10–11 AM PT

🗣 Speakers:

1. Matthew Wendel, Principal Solutions Consultant, @Simform

2. Jordan Adeboye, Cloud and AI Platforms Specialist, @Microsoft

3. Anamika Shaw, Sr. Data Architect, @Simform

#EnterpriseAI

👉 Register here for webinar: simform.com/lp/webinar-how…

Most enterprise AI programs don't fail because the ambition is wrong.

They fail because the data layer, the agents, and the governance were never built to work together.

The pilot works.
The demo impresses.
Then the handoff to production begins, and the gaps appear fast.

The textualized enough for the agent to reason reliably.

The agent logic that worked in a controlled environment breaks under real workload conditions.

Governance frameworks are stitched together after the fact, not designed in from the start.

And leadership starts asking the same question every quarter: "Why haven't we shipped anything?"

The problem isn't the model. It isn't the talent. It's that the stack was never designed as a system.

Microsoft Fabric, Copilot Studio, and AI Foundry are purpose-built to close that gap. But only when they are connected deliberately, with a data foundation that can support agents and governance that can survive an audit.

On July 9, @Simform and @Microsoft experts will walk through exactly how enterprises make that connection, from scattered pilots to production-grade AI systems.

📅 July 9, 2026 | 10–11 AM PT

🗣 Speakers:

1. Matthew Wendel, Principal Solutions Consultant, Simform

2. Anamika Shaw, Sr. Data Architect, Simform

3. Jordan Adeboye, Cloud and AI Platforms Specialist, Microsoft

#MicrosoftFabric #AgenticAI #MSPartner

Simform has been recognized as a Seasoned Vendor in AIM Research's PeMa Quadrant: Top Generative AI Service Providers 2026.

AIM Research evaluates generative AI service providers on market penetration (Pe) and technology maturity (Ma). Seasoned Vendors are recognized for strong consulting expertise, delivery maturity, and meaningful market impact.

This recognition reflects Simform's ability to connect GenAI to the systems and workflows enterprises already run on.

This recognition reflects Simform's engineering-led approach to closing that gap by connecting GenAI to the systems, data, and workflows enterprises already run on.

Here is what this recognition is built on:

- ThoughtMesh, our enterprise GenAI framework, is closing the gap between proof of concept and production deployment

- Accelerators including TrueMorph, CodeTools, and NeuVantage spanning data modernization, developer productivity, and AI workflows

Thank you to AIM Research for including @Simform through their independent assessment, and to every Simform member who built and delivered the work behind it.

Read the full story here: finance.yahoo.com/sectors/techno…

Most organisations are ready to invest in AI. Their data is not.

This is the pattern we see across retail and manufacturing engagements:

- Over a third of retail organisations are not yet ready to begin their AI adoption journey, and the bottleneck is not budget or intent

- POS, IoT, and supply chain systems creates inconsistencies, duplicates, and gaps that make a trustworthy AI foundation impossible to build

- The cost of running and maintaining these fragmented legacy systems keeps growing, while the decisions they support stay a day old or worse

The real AI barrier is not the model. It is the data sitting underneath it.

In this video, Anamika Shaw, Sr. Data Architect at @Simform, Rachael Villalaz, Cloud & AI Specialist at @Microsoft, and Matthew Wendel, Principal Solutions Consultant at @Simform, cover how manufacturing and retail organisations can build a governed, AI-ready data foundation using Microsoft Fabric.

#MSPartner #MicrosoftPartner #MicrosoftFabric

Gartner predicts 40% of organizations deploying AI will use AI observability to monitor model performance by 2028.

Everyone's reading this as a "buy a tool" forecast.

They're wrong about what it actually means.

Simform has been recognized as an Aspirant in Everest Group's Software Product Engineering Services PEAK Matrix® Assessment 2026, featured in both the Global and EMEA editions.

@EverestGroup evaluates 52 global engineering service providers across this matrix on market impact . Being included reflects Simform's growing momentum in helping enterprises, ISVs, and digital-native businesses design, build, and scale modern software products.

We are grateful to Everest Group for this recognition and to every @Simform member who makes this possible.

Here is what this recognition is built on:

- PexAI brings AI-native practices across the full SDLC, backed by accelerators like NeuVantage, CodeTools, and ThoughtMesh for faster modernization and Agentic AI delivery

- A "customer zero" delivery approach where Simform validates AI-native and agentic SDLC practices within its own engineering workflows before extending them to clients

- Co-engineering pods spanning frontend, backend, platform, and quality, embedded within client product organizations and aligned to measurable outcomes

- Enablement offerings and AI-native GCCs to help enterprises and ISVs adopt AI-driven SDLC practices and build India-based engineering centers that deliver long-term value

Read the full Everest Group report: everestgrp.com/report/egr-202…

Legacy modernization and AI production governance are not different but are the same infrastructure problem.

At Red Hat Summit 2026, the announcement by @Microsoft and Red Hat around ARO (Azure Red Hat OpenShift) was not primarily about a new Kubernetes release. It was about a cy VMs and containerized AI workloads side by side, under the same identity controls, the same compliance policies, and the same operational model.

There are major consequences for engineering teams running a sequential roadmap, meaning modernization in Phase 1 and AI governance in Phase 2.

Because you are not running two projects. You are accumulating two separate compliance burdens.

Governance-by-default is now the baseline expectation.

The platform decision your team makes this quarter determines whether your AI workloads and your legacy estate share a compliance model or accumulate two.

At @Simform, when we work with engineering leaders on migrations & modernizations, the constraint we keep encountering is not the migration tooling itself. It is the upstream assessment bottleneck: which workloads move first, at what refactoring cost, and in what sequence.

𝐍𝐞𝐮𝐕𝐚𝐧𝐭𝐚𝐠𝐞, our AI-powered modernization accelerator, is specifically built to compress that assessment cycle so teams can make the platform transition without the months of manual triage that typically slow it down.

This does not mean modernization got easier. It means the cost of keeping it sequential just got higher.

#MSPartner #MicrosoftPartner

Your first 10 AI agents worked. Your next 50 probably won't, and the reason has nothing to do with the models.

The first wave of agents succeeds because informal governance holds them together.

Someone knows what each agent does,
roughly what it costs,
what data it touches,
and imity creates stability. It is not a system; it is human attention acting as a system.

Cross 50 agents, and that model breaks. No single person can hold the full picture anymore.

Agent identity starts to blur. Ownership fragments across teams. Agents hand off work to other agents without structured contracts, so interaction volume grows faster than agent count.

Enterprises end up paying for conversations no one designed, authorized, or measured.

Meanwhile, access permissions quietly expand. Outputs accumulate with no traceable audit trail. And the AI spend that looked forecastable at 10 agents becomes unpredictable at 50.

@Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027, not because the agents fail to work, but because the operating model around them does not exist.

At @Simform, we see this inflection point consistently. We built 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐌𝐞𝐬𝐡 as a reference architecture specifically for what breaks here: agent identity, governance boundaries, evaluation, and cost attribution at fleet scale.

Scaling agents is the easy part. Building the governance architecture that keeps 50 of them from compounding your risk is where the real engineering work starts.

Simform has been recognized as a 'Pervasive Player' in the Application Modernization Services Market by @marketsmarkets on its 360Quadrants platform — one of only 35 vendors selected from 200+ evaluated globally. 🧵

Most organisations believe they're ready to adopt GenAI. But their data says otherwise.

McKinsey found that 63% of Chief Data Officers report they don't have the right data foundation to adopt generative AI.

Here's what that actually means for your organization

Most enterprises are not struggling with a lack of data automation.

They are struggling with slower, more expensive data execution as scale increases.

Here is why #AIready #DataOps is the answer most teams are not ready for. 🧵

IDC projects AI infrastructure costs will run 30% over budget by 2027.

Agent usage: 10x.
Inference demand: 1000x.
Cloud waste at baseline: 20 to 30%.

AI doesn't create new cost problems.
It amplifies the ones you haven't solved.

Here's what's actually happening. 🧵

Lift-and-shift feels like the safe choice when migrating to the cloud.

But it rarely is.

Anamika Shaw, Sr. Data Architect at @simform, shares what happens across real customer migrations to @Microsoft Fabric!

#MSPartner #MicrosoftFabric #MicrosoftPartner

Fabric is not a platform upgrade. It's an architecture decision. And most teams are making it without cleaning up what they already have.

So, here's what you should decide next:

Enterprises aren't accelerating software delivery by hiring more engineers anymore. They're doing it by rethinking whether AI is embedded across SDLC or is just sitting at the edges.

The industry signal is now concrete.

Most teams migrating to the cloud assume SSIS pipelines will carry over cleanly.

They don't.

Data Factory, Fabric's built-in integration engine, is a full rethink of how data pipelines should work.

Matthew Wendel breaks down exactly how this translation works in practice.

#FABCON2026 is a wrap, and what a week it was.

Great conversations, great energy, and a lot of exciting ideas to bring back to the table.

We look forward to connecting again soon.

#MicrosoftFabric #FABCON

@simform is now a Microsoft Azure Expert Managed Services Provider (MSP), a designation held by fewer than 105 companies worldwide out of 400,000+ Microsoft partners (only 0.03%), independently audited against Microsoft's highest standards.

#MSPartner #MicrosoftPartner #MAICPP

@simform and @Microsoft are hosting a live webinar on modern, governed migration patterns using Azure + Microsoft Fabric, so your Azure move supports analytics and AI readiness from day one.

📅 March 12 | 10:00 AM PST (Online)

Enterprises are moving from AI pilots to operating models. The winners will be the ones who can scale safely, not just ship quickly.

That’s why @simform is strengthening its @Microsoft partnership with a $3M investment to help teams scale safely and repeatably on Azure.

Azure governance can pass every audit, but cost allocations don't tie out, and nobody can explain why.

Most enterprise teams are asking: "Why do all these AI assistants we already built/bought not talk to each other?"

Individually, they look useful, but collectively, they create friction due to duplicated work, inconsistent answers, & unclear ownership when something goes wrong.

Simform has earned the Analytics on Microsoft Azure specialization.

What does this mean for your business?

- Get a clear, execution ready analytics plan with target architecture, data domain mapping, & delivery sequencing.

Microsoft Ignite 2025 confirmed a clear shift: AI agents are no longer experiments.

They are becoming enterprise infrastructure; systems that act, coordinate, & execute across workflows.

2 developments make this transition explicit:

Last week, our team reviewed a client's new AI agents, which performed flawlessly in demos but were chaotic in production.

Nothing was wrong with the agents. Just their data foundation wasn’t ready.

Buying Azure directly from Microsoft puts these burdens on your teams:

- Tracking consumption
- Handling support escalations
- Managing multiple license types
- Adapting to frequent Azure service & policy updates

That’s why Microsoft recommends working with CSPs

Thank you to everyone who visited us at Microsoft Ignite 2025.

It was great meeting so many teams, hearing about your projects, and discussing where AI, data, and modernization work fit into your upcoming roadmaps.

We’re at Microsoft Ignite 2025, doors are open.

If you’re at Moscone Center, stop by Booth #5439L to meet our experts and talk through your plans for AI, modernization, data platforms on Azure, and leveraging our accelerators.

Microsoft Ignite 2025 is just around the corner.

Stop by our Booth #5439L to meet Simform’s product-engineering leaders and see how we help teams move from AI pilots to production on Azure.

📅 Nov 18–21
📍 Moscone Center, San Francisco
🔗 Reserve time: simform.com/lp/microsoft-i…

Organizations struggle to adopt Azure OpenAI - identifying use cases, selecting right models, lacking enterprise-grade security & governance requirements

@simform provides this structured approach to validate high-impact AI use cases & deliver functional prototypes

Simform is now live on the Microsoft Ignite Digital Showcase.

🔗 Explore the Showcase: ignite.microsoft.com/en-US/sponsors…

📍 Moscone Center, San Francisco
📅 Nov 18–21
➔ Booth #5439L

Modernizing data warehouses with AI:
Self-healing pipelines, reliable analytics, and real business impact

👉 Register now for this webinar: simform.com/lp/webinar-dwh…

Simform is proud to be a Sponsor at Microsoft Ignite 2025!

Stop by our Booth to see how we leverage Azure, agentic AI, accelerators, & disciplined engineering to reduce costs, speed releases, & improve customer experience.

Moscone Center, San Francisco
Nov 18–21
Booth #5439L

Gartner research reveals that less than 30% of leaders are pursuing enterprise-level Gen AI initiatives capable of industry-wide disruption.

The AI productivity boom we all experienced was just the beginning.

@simform’s Azure app & database migration experts implement strategies aligned with Azure Well-Architected Framework to ensure your applications & databases are planned & designed for scale, security, & automation.

Here’s what you get:

To help you mitigate these challenges, @simform does a holistic assessment of your cloud networking profile around the following key aspects & suggests the right strategy!

Most retailers aren't "data-poor". They're prediction-poor because fragmented systems prevent the unified customer insights needed for proactive inventory decisions.

Here's how they can lead the transformation from reactive to proactive inventory management 👇

For a leading insurer in Scandinavia, we built end-to-end vehicle tracking & fleet management solution, leveraging modern cloud architecture & data-driven insights.

They wanted to revolutionize their auto insurance operations.

Modernizing applications isn’t just about moving to the cloud.

Simform's Application Modernization Assessment provides a clear roadmap to help you navigate this transition with confidence.

Simform is now an official IBM Silver Partner

It is our strategic entry into IBM Partner Plus program with commitment to building future-proof digital products for high-growth ISVs & tech-enabled enterprises with our deep engineering DNA & IBM's enterprise-grade tech platform.

Simform has earned the Infra and Database Migration to Microsoft Azure Specialization!

This validates our proven expertise in migrating Windows Server, SQL Server, Linux VMs (RHEL/SUSE), and open-source databases (PostgreSQL, MySQL, MariaDB) to Azure.

Real-time retail success isn't about faster dashboards.

It's about building intelligent data platforms that turn every customer interaction into a competitive advantage.

Here's an AI-enabled data platform modernization roadmap that can transform retail operations.

Healthcare loses Billions annually because systems are disconnected.

Tech leaders need platforms that scale, yet fragmented EHR interfaces delay care, inflate costs, and create safety risks.

Here’s a plan to unlock FHIR-first interoperability:

Simform has earned the Kubernetes on Microsoft Azure Specialization!

With a team of Azure-certified professionals and our co-engineering model, we remain committed to turning your containerization roadmap into measurable business outcomes.

With our deep engineering DNA and unique co-engineering delivery model, we’re committed to building future-proof digital products for high-growth ISVs and tech-enabled enterprises.

Simform has been named a Clutch Global Award winner for Spring 2025.

We ranked #3 in the Custom Software Development category from the 41,884 tech companies (and increasing), setting the benchmark for excellence in the B2B services space.

Simform has earned the AI Platform on Microsoft Azure Specialization!

With a team of Azure-certified professionals, we remain committed to helping organizations turn ambitious AI strategies into measurable results.

Simform is a 2025 @trustradius Top Rated Award winner.

This achievement took deliberate effort, iterating fast, and making transparency a non-negotiable.

Use this 5-step MLOps framework to get sustainable healthcare AI at scale:

1. Align AI with strategic KPIs: Map initiatives directly to metrics like cost reduction or faster diagnosis. Pre-validate against HIPAA, GDPR, and HHS fairness.

Microsoft Build 2025 made one thing clear: AI-first product engineering is officially mainstream.

Here are 9 updates that you shouldn’t miss:

1. Copilot Agents turn “peer programmer”—auto-modernize .NET / Java apps and resolve SRE incidents from inside @github.

2. Azure AI models (incl. Grok 3 and the full @MistralAI lineup) with a router that picks the best model per call.

3. Foundry Local and Windows AI Foundry bring the same catalog and LoRA fine-tuning to every laptop (Windows and Mac) — even offline.

4. Fabric adds no-code Digital Twins and AI-driven OneLake transforms to slash data-to-insight cycles.

5. @VisualStudio and VS Code refresh—monthly VS releases, multi-window VS Code, and Copilot open-sourced into the core repo.

6. Autonomous SRE agent triages, mitigates, and files repair issues—shrinking MTTR without extra headcount.

7. @nvidia GB200 on Azure pushes 865k Tokens/s, backed by a 400Tb/s AI WAN and zero-water liquid cooling.

8. Enterprise-grade guardrails — Entra Agent ID, Defender for Cloud, and Purview lineage wrap every agent and model.

9. Agent Store + Copilot Studio canvas lets teams publish and orchestrate custom AI workers across @Microsoft365 and @MicrosoftTeams.

@Microsoft just collapsed code, data, and AI ops into a unified developer-agent stack. Now, companies can leap from PoC to production in weeks, not quarters, if they have the right engineering partner to steer the build.

Simform achieves Datadog Standard Partner status.

This partnership validates our expertise in implementing comprehensive observability solutions that provide total visibility across your entire technology stack.

What does this mean for your business?

- Gain unified visibility plications, and user experiences across hybrid and multi-cloud deployments - from VMs to Kubernetes.

- Detect and resolve bottlenecks in real-time with AI-driven anomaly detection, reducing downtime risks before they impact operations.

- Leverage Datadog’s Flex Logs with our Azure-native implementation to decouple storage and query costs, retaining critical data without overspending.

- Through a comprehensive support model, get our guidance on the latest features, roadmap insights, and prioritized troubleshooting from Datadog, ensuring seamless and faster integration with your Azure ecosystem.

With our deep engineering DNA and Datadog's (@datadoghq) powerful observability platform, we're ready to help you gain comprehensive insights across your infrastructure, applications, and user experience.

Buying Azure directly from Microsoft puts these burdens on your team
- monitoring usage
- resolving all issues
- managing multiple licenses
- staying up-to-date with rapid platform changes

That’s why Microsoft recommends working with CSPs to simplify cloud operations.

Simform has earned the Build AI Apps on Microsoft Azure Specialization!

This validates our ability to design, build, and scale AI-driven applications across Azure’s AI, app platform, and data services.

What does this mean for your business?

- Accelerate AI innovation with our frameworks (including Azure OpenAI and Cognitive Services) to launch GenAI use cases in weeks, not quarters.

- Deploy confidently using enterprise-grade security, compliance, responsible AI practices, and sector regulations like HIPAA and GDPR in every solution.

- Offset initial costs with Microsoft funding and accelerate ROI through our co-engineering approach.

With a team of Azure-certified engineers and a co-engineering model focused on measurable outcomes, we’re ready to help you turn AI roadmaps into real-world value.

@msPartner

Most lenders still spend 60–90 days closing a mortgage—because 80% of that time is wasted on document wrangling and manual reviews.

But in today’s rising-rate environment, every extra day costs you capital, customers, and market share.

What if underwriting wasn’t a backlog, but gine?

Navigating cloud migration comes with challenges like over-provisioned servers, lengthy procurement cycles, and high IT costs.

Without expert guidance, you risk compatibility issues, data integrity problems, and extended business downtime during cloud transitions.

Simform's experts can help you seamlessly transition databases and workloads to the cloud while ensuring security and regulatory compliance.

Simform has earned the Advanced Specialization for Accelerate Developer Productivity with Microsoft Azure!

This validates our ability to help development teams build, manage, and scale cloud-native apps faster with Azure Developer tools.

What does this mean for your business?
ed using GitHub Copilot, integrated directly into your existing workflows for maximum efficiency.

- Streamline the DevOps lifecycle with pre-configured environments, shift-left feedback, and AI-powered remediation, enabling fast, compliant, secure, and scalable app delivery.

- Unify your development experience by eliminating scattered tools, minimizing context switching, and reducing tech debt.

With a team of Microsoft-certified professionals, we are committed to continuing our journey toward helping organizations achieve seamless and scalable developer operations.

Businesses are thrilled by the cloud’s speed & flexibility but quickly run into security issues like misconfigurations, lack of visibility, & compliance gaps.

Here’s how @Simform addresses these critical issues effectively:

1. Prioritize Encryption
- Prioritize encryption to protect t, & in use, ensuring data remains safe even if a breach occurs.

2. Unified Multi-Cloud Strategy
- Implement a consistent security framework across all cloud environments to streamline and secure the infrastructure.

3. Secure Systems Integration
- System integrations are secured using standardized APIs & unified IAM to ensure consistent authentication.

4. Policy & Process Reinforcement
- Manage & monitor the cloud environment with regular audits & compliance checks to maintain robust security practices.

5. Proactive Threat Monitoring & Response
- Deploy real-time detection & automated alerts to address potential breaches swiftly.

What's your biggest challenge as your cloud infrastructure becomes complex - compliance management, visibility into threats, or maintaining consistent security policies across platforms?

Organizations constrained by aging applications & databases face high maintenance costs and diminishing performance.

Simform’s Azure app & database migration experts implement strategies aligned with Azure Well-Architected Framework to ensure your applications & databases are planned & deity, & automation.

Jumping into Generative AI without a plan leads to wasted time & resources.

Here’s how to ensure a successful Proof of Concept (PoC):

Ignoring security in app modernization risks critical breaches that could devastate entire systems before full operation.

Here’s a 6-step security blueprint to secure your system from day one:

1. Zero-Trust Architecture: Implement a zero-trust model to verify every user and authentication and minimizing unauthorized access.

2. Security Automation: Utilize tools like Terraform to automate security configurations. Automation reduces human error and maintains consistent security policies throughout your application lifecycle.

3. Continuous Monitoring: Deploy solutions such as Azure Security Center for real-time threat detection. Proactive monitoring allows you to identify and address vulnerabilities before they escalate.

4. Encryption Best Practices: Encrypt sensitive data both in transit and at rest using AES-256 standards. This ensures that only authorized parties can access critical information.

5. Regular Penetration Testing: Conduct regular penetration tests to proactively identify and remediate system weaknesses, strengthening your defenses against potential attacks.

6. Multi-Factor Authentication (MFA): Enforce MFA across all access points to add an extra layer of security, effectively preventing unauthorized access even if credentials are compromised.

🔁 Repost this if you believe security should be the foundation of your app modernization strategy, not an afterthought.

#AppModernization #CloudSecurity #CyberSecurity #simform

@haider1 🤷‍♀️

There's one bottleneck in Healthcare.

Deciding what to SHOW & HIDE is a dilemma out of tons of data.

It means a difference between life and death.

Still, how do leading hospitals make sense of it all so quickly?

The answer lies in AKS and Azure Cosmos DB, delivering results whens break it down:

🔹Step 1: Data Ingestion

Sensors and monitoring devices generate real-time patient data. This data flows seamlessly through Azure API Management into a microservices architecture hosted on AKS.

🔹 Step 2: Data Storage

An ingest service stores the data in Azure Cosmos DB, a highly scalable database designed for large datasets.

🔹 Step 3: Real-Time Analytics

Using Apache Kafka on HDInsight, the analysis service streams critical data to data scientists. ML models on HDInsight and platforms like Splunk analyze this data for trends and anomalies.

🔹 Step 4: Processing and Insights

A processing service stores results in Azure Database for PostgreSQL and Azure Cache for Redis, ensuring fast access to processed data.

🔹 Step 5: Visualization and Decision Support

A web app powered by Azure App Service creates visual dashboards for healthcare professionals, helping them make real-time, data-driven decisions.

With AKS and its supporting Azure ecosystem, healthcare organizations can:
✔️ Ensure faster response times in emergencies
✔️ Enhance patient care with predictive analytics
✔️ Scale efficiently as data sources increase

This is just one example of how technology meets healthcare innovation, enabling better outcomes for patients.

What are your thoughts on leveraging data streaming in critical industries?

#DataStreaming #HealthcareInnovation #IoT #CloudComputing #Azure

2020: Banks Questioned AI's ROI
2024: Banks without AI lose $50M annually

And leaders are already there:
- Wells Fargo cut fraud by 35%
- JPMorgan saves $150M/year with AI
- Goldman Sachs automated 50% of trades

The industry is moving fast and the numbers are clear:

The global ll grow from $9 billion in 2023 to $37.15 billion in 2028 at a CAGR of 32.8%.

The surge is driven by investments in predictive analytics, AI-powered compliance tools, and personalized banking experiences.

And here’s where forward-thinking organizations are focusing:

1. Customer engagement: AI chatbots and voice assistants are now table stakes for round-the-clock customer support.

Action Plan:
↪ Deploy AI chatbots for top 20 customer queries
↪ Implement voice authentication systems
↪ Set up 24/7 automated response channels

2. Risk mitigation: Predictive analytics and fraud detection systems are transforming operational security.

Action Plan:
↪ Install real-time fraud detection systems
↪ Implement automated transaction monitoring
↪ Deploy predictive risk scoring models

3. Wealth management: Robo-advisors are delivering tailored financial advice, making high-end services accessible to more users.

Action Plan:
↪ Launch automated portfolio management tools
↪ Develop AI-driven investment recommendations
↪ Create personalized financial planning systems

The question is no longer if AI is the right move. It’s about how soon you can adapt it to remain competitive.

#Banking #ai #DigitalTransformation #Fintech #CustomerExperience #Simform

9. @Withings Omnia mirror gives 360-degree body scans for a complete health profile.

8. @Halliday_Global Smart Glasses: Cutting-edge smart glasses with bold features—though some mixed reviews on design and function.

7. @UltrahumanHQ Smart Ring: An 18-karat gold ring that tracks your health while doubling as a stylish accessory.

6. @LGUS StanbyME 2: The ultimate portable TV, perfect for on-the-go entertainment with a sleek new design.

5. @nvidia $3K AI supercomputer—unleashing the power of AI with every task.

4. @SwitchBot K20+Pro: A robot vacuum that cleans, purifies air, acts as a security camera, and even delivers items. Smart home game-changer.

3. @XPENG_AEROHT flying car prototypes hint at a future where personal flight is a reality.

2. @Lenovo ThinkBook Plus Gen 6: A laptop with an expanding screen, designed for ultimate multitasking and flexibility.

1. @nvidia RTX 50-Series GPUs: Supercharged graphics for gamers and pros, promising massive performance upgrades.