Pinned Tweet
We've been pretty quiet about what we're building. That changes now.
Our reasoning framework is currently beating every @OpenAI model on industry standard benchmarks. There are six models in development. SERV-nano just matched GPT-5.4 at 20x lower cost and 3x the speed. The research paper backing it is in peer review at a top-1% AI journal. The UAE government is running it in production, so are 10+ enterprises.
Nothing comes even close.
This goes far beyond any wrapper or prompt engineering gimmick, we've developed an entire AI reasoning layer from scratch: structured, bounded, deterministic using machine readable code instead of vague english prompts.
Any builder or enterprise swaps two lines of code and their agents get much cheaper and much smarter instantly. The self-serve API is about to open, in a multi-phase rollout.
More soon.
Our reasoning framework is currently beating every @OpenAI model on industry standard benchmarks. There are six models in development. SERV-nano just matched GPT-5.4 at 20x lower cost and 3x the speed. The research paper backing it is in peer review at a top-1% AI journal. The UAE government is running it in production, so are 10+ enterprises.
Nothing comes even close.
This goes far beyond any wrapper or prompt engineering gimmick, we've developed an entire AI reasoning layer from scratch: structured, bounded, deterministic using machine readable code instead of vague english prompts.
Any builder or enterprise swaps two lines of code and their agents get much cheaper and much smarter instantly. The self-serve API is about to open, in a multi-phase rollout.
More soon.
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currently building a customer deck with opus 5.5 and I feel like I have superpowers...
crazy to think that just 2 years ago we were jumping around like chimpanzees when one of our engineers at OpenServ got an agent to log into gmail by itself.
let the good times roll
crazy to think that just 2 years ago we were jumping around like chimpanzees when one of our engineers at OpenServ got an agent to log into gmail by itself.
let the good times roll
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On the morrow 🫡
We’re entering a new paradigm where AI agents make decisions and take actions that demand reliable reasoning.
Tomorrow at 3 PM UTC @open_founder hosts @reppo and @GoKiteAI on Spaces to talk agentic payments, AI data markets, and verifiable agents.
Set your reminder below.
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Builders... build!
SERV Hackathon 02 is live.
Build with SERV Reasoning + @dphnAI, @GoKiteAI, @reppo or bring your own idea to the Open Track.
Two weeks to cook across AI inference, agentic payments, AI data markets, and more.
Start here: openserv.ai/hackathon-2
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Tim retweeted
SERV brings @dphnAI, @GoKiteAI, and @reppo into the lab.
Pair their AI infra with SERV Reasoning to get more from smaller models, cut costs, and make every agent decision auditable.
SERV Hackathon 02 kicks off Monday. Pre-register now: openserv.typeform.com/registerhack02
Pair their AI infra with SERV Reasoning to get more from smaller models, cut costs, and make every agent decision auditable.
SERV Hackathon 02 kicks off Monday. Pre-register now: openserv.typeform.com/registerhack02
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Tim retweeted
The next major leap for SERV Reasoning is coming with SERV v3: Graph Sharding.
We’re preparing the next builder cohort to test it, building on feedback from the first beta users as we move toward a wider release.
In this walkthrough, our CTO @dashersw talks with builders and action, exploring how teams can inspect an agent workflow, spot drift, and see how a change at one step affects everything downstream.
That visibility gives developers more ways to understand, refine, and scale their AI workflows. Builder conversations and tests are helping us push Graph Sharding toward production, with more control over how complex workflows run.
We’re building SERV Reasoning for enterprise AI, the agentic economy, and the next wave of AI applications.
Apply to join the next beta builder cohort and help shape Graph Sharding: openserv.typeform.com/graphsharding
We’re preparing the next builder cohort to test it, building on feedback from the first beta users as we move toward a wider release.
In this walkthrough, our CTO @dashersw talks with builders and action, exploring how teams can inspect an agent workflow, spot drift, and see how a change at one step affects everything downstream.
That visibility gives developers more ways to understand, refine, and scale their AI workflows. Builder conversations and tests are helping us push Graph Sharding toward production, with more control over how complex workflows run.
We’re building SERV Reasoning for enterprise AI, the agentic economy, and the next wave of AI applications.
Apply to join the next beta builder cohort and help shape Graph Sharding: openserv.typeform.com/graphsharding
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SERV v3 is live for the first cohort of beta testers!
The result of everything we've learned since the API beta went live in early summer - serving as an upgrade that directly caters to the demands of enterprise clients looking to implement AI agents at scale.
The result of everything we've learned since the API beta went live in early summer - serving as an upgrade that directly caters to the demands of enterprise clients looking to implement AI agents at scale.
SERV v3 is now live for the first builder cohort.
Graph Sharding lets developers map AI workflows, inspect why decisions happen, and shape how each step runs: LLMs for open-ended tasks, deterministic code for bounded ones.
SERV is building the command center for agent systems.
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Tim retweeted
the @openservai team has been sitting down with serious people in the industry, CTO @dashersw met akar from neol to talk about ai reasoning, decision models and why current agent systems still fall short of enterprise and government expectations, then tested graph sharding on a roduction task went from 7 seconds as a single llm call to 2.5 seconds, and CTO armagan is upfront that it’s a small set of prompts and not a benchmark, which is exactly why i trust it
then there’s abdul hadi asif, regional partner at cervana ai, he has launched products like cervana ai, arbrr, onboard and his profile lists @GoogleStartups, @AWSstartups and @nvidia behind his work, so he’s someone who ships ai products for a living, after talking with tim @open_founder and CTO @dashersw he tested openserv himself and called it genuinely convenient to integrate, of which i consider such comment a builder’s verdict instead of a pitch deck
the doors keep opening for developers too, openserv is now featured on the base builder stack and base builders get $30 in free serv reasoning api credits, and hackathon 02 pre-registration is open with $5 in credits, with @dphnAI, @GoKiteAI and @reppo as track partners, sign up before it fills up 👇
openserv.typeform.com/registerhack02
then there’s abdul hadi asif, regional partner at cervana ai, he has launched products like cervana ai, arbrr, onboard and his profile lists @GoogleStartups, @AWSstartups and @nvidia behind his work, so he’s someone who ships ai products for a living, after talking with tim @open_founder and CTO @dashersw he tested openserv himself and called it genuinely convenient to integrate, of which i consider such comment a builder’s verdict instead of a pitch deck
the doors keep opening for developers too, openserv is now featured on the base builder stack and base builders get $30 in free serv reasoning api credits, and hackathon 02 pre-registration is open with $5 in credits, with @dphnAI, @GoKiteAI and @reppo as track partners, sign up before it fills up 👇
openserv.typeform.com/registerhack02
SERV Reasoning is the intelligence layer for the agentic economy.
Pair SERV with infra from @dphnAI @GoKiteAI @reppo to build agents that perform better, cost less, and are fully verifiable.
Pre-registration is open. Sign up now to get $5 in credits: openserv.typeform.com/registerhack02
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SERV 🤝 Base builders
OpenServ joins the Base Builder Stack.
Base builders can now leverage SERV Reasoning to build more reliable AI agents and automate complex workflows with frontier-level performance at a fraction of the cost.
Claim free inference credits: openserv.typeform.com/servcreditsbase
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bing bong!
SERV Reasoning is the intelligence layer for the agentic economy.
Pair SERV with infra from @dphnAI @GoKiteAI @reppo to build agents that perform better, cost less, and are fully verifiable.
Pre-registration is open. Sign up now to get $5 in credits: openserv.typeform.com/registerhack02
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Tim retweeted
We’re joining @openservai’s SERV Hackathon 02 as a track partner, alongside @dphnAI and @reppo.
Build with Kite Agent Passport:
▷ Verifiable identity
▷ User-defined permissions and spending limits
▷ Agentic payments
More details next week. Come build on Kite. 🪁
Build with Kite Agent Passport:
▷ Verifiable identity
▷ User-defined permissions and spending limits
▷ Agentic payments
More details next week. Come build on Kite. 🪁
Introducing SERV Hackathon 02 track partners:
@dphnAI @GoKiteAI @reppo
From inference and agentic payments to AI data markets, add SERV to your AI stack and build more reliable agents at lower cost.
Hackathon info drops next week.
Build with SERV: openserv.ai
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More partners, more builders, more SERVing.
Hackathon edition 02 coming up!
Hackathon edition 02 coming up!
Introducing SERV Hackathon 02 track partners:
@dphnAI @GoKiteAI @reppo
From inference and agentic payments to AI data markets, add SERV to your AI stack and build more reliable agents at lower cost.
Hackathon info drops next week.
Build with SERV: openserv.ai
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Tim retweeted
Murmur brings a new layer of accountability to the agentic economy, powered by SERV.
@murmurappx is building verifiable track records for AI agents through sealed market predictions, transparent scoring, and public leaderboards.
Going live this Friday: launch.openserv.ai
@murmurappx is building verifiable track records for AI agents through sealed market predictions, transparent scoring, and public leaderboards.
Going live this Friday: launch.openserv.ai
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Your AI agents may be expensive for the wrong reason.
Most companies force one frontier model to handle every step, including decisions that don't need it.
We added Jev nodes to SERV Reasoning for fast, structured judgments at a fraction of the cost.
If you run agents at ee this:
Most companies force one frontier model to handle every step, including decisions that don't need it.
We added Jev nodes to SERV Reasoning for fast, structured judgments at a fraction of the cost.
If you run agents at ee this:
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SERV v3 has leap-frogged the entire AI agent space.
With v3, we're taking SERV Reasoning far beyond an API, toward a full suite for building, managing, improving and auditing enterprise agent systems.
Graph Sharding (aka v3) is the next step toward solving the problems that have been holding enterprises back from deploying agents at scale: unpredictable costs, reliability, compliance requirements, and lack of control. And critically, pushing towards the elusive 99.9% agent reliability that everyone is chasing... Well now it's here.
On top of the release, we're expanding distribution through enterprise channels like AWS Marketplace, pushing toward new partnerships, and continuing to build out $SERV utility as the agentic economy takes shape.
Proud of the team and the trajectory we're pushing on.
Onwards.
With v3, we're taking SERV Reasoning far beyond an API, toward a full suite for building, managing, improving and auditing enterprise agent systems.
Graph Sharding (aka v3) is the next step toward solving the problems that have been holding enterprises back from deploying agents at scale: unpredictable costs, reliability, compliance requirements, and lack of control. And critically, pushing towards the elusive 99.9% agent reliability that everyone is chasing... Well now it's here.
On top of the release, we're expanding distribution through enterprise channels like AWS Marketplace, pushing toward new partnerships, and continuing to build out $SERV utility as the agentic economy takes shape.
Proud of the team and the trajectory we're pushing on.
Onwards.
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99% agent reliability at scale is what we’re pushing toward with SERV v3.
We’re turning SERV into a full operating system for agents, where builders can inspect, configure, and trust their agents’ reasoning structures.
The beta is coming soon for a select group of early testers - getting closer each day!
We’re turning SERV into a full operating system for agents, where builders can inspect, configure, and trust their agents’ reasoning structures.
The beta is coming soon for a select group of early testers - getting closer each day!
SERV Reasoning delivers frontier-level performance with smaller models, at a fraction of the cost.
v3 takes SERV further with agent graphs, inspectable reasoning, and near-zero-cost decisions.
@open_founder presenting SERV at gm AI v2 in Singapore ↓
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From day one, our goal at @openservai has been to make SERV capture value from the activity generated across our products and network.
As we continue scaling SERV Reasoning and push adoption across enterprise AI and the agentic economy, we're working to strengthen that connection.
One more piece is coming together for SERV.
As we continue scaling SERV Reasoning and push adoption across enterprise AI and the agentic economy, we're working to strengthen that connection.
One more piece is coming together for SERV.
Pay with ethereum:0x40e3d1a4b2c47d9aa61261f5606136ef73e28042 is live.
Builders and enterprises can now use the SERV token to purchase SERV Reasoning API credits at a 15% discount compared to traditional payment methods.
75% of SERV received through payments will be burned, allocated to the treasury.
This marks another step in expanding SERV's utility as the native currency of the SERV ecosystem, with more use cases to come as we bring new products and services to market.
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SERV reasoning changes the game for Vertical AI startups and enterprise.
So far, agent reliability remains a major barrier to scaling AI workflows.
An agent that fails 20% of the time is nowhere near good enough. The usual fix is a much more expensive model. SERV offers another mer comparison, costs were around 90% lower, with no failures reported so far, down from a 5–10% failure rate.
This is how:
So far, agent reliability remains a major barrier to scaling AI workflows.
An agent that fails 20% of the time is nowhere near good enough. The usual fix is a much more expensive model. SERV offers another mer comparison, costs were around 90% lower, with no failures reported so far, down from a 5–10% failure rate.
This is how:
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