Tim @open_founder

@cobotgg @openservai @lucashafner This is sick. Nice work

SERV Reasoning Private Beta is accelerating and a new batch of builders is coming on board, pulling the next ones in. The pattern holds: • Lower costs • 100% reliability • Faster than their old stack Here are a few recent additions to the program. -> Apply to join now 👇

@AlgodTrading

@cz_binance 🫡

Bento is now integrated with SERV Reasoning by @openservai 1,004ms faster than Gemini. 5x lower cost. Same proven reliability. As AI agents gain wallets and start executing real transactions, the quality of their reasoning becomes part of the security stack. Better reasoning means: → fewer risky actions → fewer false alarms → more context-aware decisions → safer agent execution At Bento, we're building the security layer for AI agents on @solana. SERV helps agents think better. Bento helps make sure they act safely. The future won't be powered by agents alone. It will be powered by agents that can reason and execute securely. Live integration in our Beta. Check it out 👇

@openservai has a launchpad, but this was built in response to teams building in our ecosystem on top of SERV Reasoning This is the core product, and a key differentiator of SERV launches - verifiable tech MOAT For an AI powered business, the cheaper you can make inference at the earliest stages, the more room you have to subsidize early user growth, which imo should lead to faster more successful GTM and better chances of finding PMF

OpenServ @openservai

3 days ago

SERV is the agentic reasoning engine solving exactly this - for enterprises, financial institutions, banks and even governments deploying AI in production. The next frontier is reasoning compression. Cheaper models reduce the cost of intelligence, but they do not solve the cost

24 71 256 16K 14

@ptservlor @openservai Hell yeah man. It's happening.

Pretty insane to see 600k+ views on this article about a relatively little known project I'll tell you why I wrote it, and it wasn't for any financial incentive (the team didn't ask me to write it, and I hold only a small amount of the token) If you've followed my posts, I've been consistently writing about the unsustainable costs of intelligence that enterprises are facing Demand for intelligence is near infinite, but only when there is ROI If everyone tokenmaxxes with the most expensive models with the highest levels of reasoning, most use cases won't find ROI What happens if we don't find ROI? If enterprises don't find ROI, we start to see an unwind of the AI trade which has massive implications across financial markets and the global economy We NEED for enterprises to find ROI, and soon So that means we need to highlight more solutions that enable enterprises to get better intelligence-per-dollar spend, and get them adopted I've been doing a LOT of research on this topic and posted a playbook for enterprises to reduce costs a few days ago (will link it in replies) And I found this project OpenServ that has a solution called SERV Reasoning just hiding in plain sight, and in crypto of all places That's what made me write about it, and I was naturally skeptical about it when I began (bc crypto) I'm glad many people found this article helpful, let's keep the cost optimization dialogue going

Kevin Simback 🍷 @KSimback

7 days ago

x.com/i/article/2059…

47 138 451 663K 217

@ptservlor Beautiful!

@dashersw Just use SERV Reasoning.

SERV worldwide.

Lucas (opn/srv) @lucashafner

6 days ago

Just came back from Kenya after a week of conversations on AI, finance, and institutional adoption. By the end of the trip, we had met with the largest investment bank in the country, half of their top 10 banks, fintechs, former ministers, and senior leaders with experience

21 38 186 43K 35

@ServReasoning @openservai Full send baby

Quite speechless to be honest. This moment represents 2+ years of building toward a very specific vision: > To become the standout crypto x AI company that breaks out into the global enterprise sphere... With agent infrastructure that services enterprises, institutions, and governments... Couldn't be more excited about where we're heading. Big thanks to Kevin for taking the time to properly understand and share what we're building at OpenServ, it means a lot.

Kevin Simback 🍷 @KSimback

7 days ago

x.com/i/article/2059…

47 138 451 663K 217

@jazzplane Haha just jokes, 7’2 would be crazy

@jazzplane 7'2 wbu?

This is the first step. Together with NEOL, we’ve begun deploying SERV Reasoning into real government-grade AI workloads, already live with the UAE government. NEOL uses AI agents to surface the right people, relationships, and institutional knowledge for governments and large institutions making high-stakes decisions. For that to work, “usually right” isn’t enough. The agent needs to be reliable, reproducible, and auditable. SERV Reasoning enabled NEOL to move from brittle prompt-based agents to structured reasoning graphs their team can inspect, test, and improve systematically, reaching 100% accuracy on key production agents. That matters because when a government client asks why a certain person was recommended, NEOL can now point to the reasoning structure behind the decision. Not a black box. Not a guess. A traceable decision process. This is the beginning of something much larger. Every enterprise, government, and public institution trying to deploy AI into serious workflows will run into the same wall: agents that are too unreliable, too opaque, and too difficult to audit. That is exactly the wall SERV Reasoning was built to break through. Our aim is to keep expanding what we unlock with NEOL, deepen the relationship across more institutional use cases, and bring this same reasoning infrastructure to the enterprises and governments that need AI they can actually trust in production. The future of institutional AI cannot run on todays infra, it needs specialized AI reasoning that can be tested, audited, reproduced, and trusted. That is the institutional gap SERV is plugging.

From the man himself… LFG

Greg @shuzeld

a week ago

Even at Google I’ve not seen this level of positive feedback on any product within a month of beta. Mind-boggling… 🤯

7 47 179 11K 12

Moar

BETTER @tradebetterapp

a week ago

MESH is the privacy-first AI router: one OpenAI-compatible endpoint in front of 46+ models, a signed receipt on every call, and zero payload retention. SERV is the reasoning layer adding structured, schema-forced, auditable reasoning that routes each step to the right model

5 15 64 5K 7

Orbit agents just got a major reasoning upgrade. Previously, we upgraded the core XONA agent with SERV Reasoning by @openservai. Now, we’re bringing the same upgrade across Orbit. All 266 agents already built on Orbit are now aligned with SERV Reasoning, giving them faster execution, lower cost, and the same reliability we benchmarked on our production workflow. This means Orbit agents can now reason, execute, and access XONA resources more efficiently across the Agentic Commerce ecosystem. Build agents with Orbit. Power them with XONA. Reason with SERV.