OpenServ

Identity

OpenServ is a full-stack AI infrastructure provider built around SERV, a deterministic reasoning engine, and BRAID, a structured-reasoning layer the project claims substantially improves benchmark accuracy over raw model inference. The roster frames OpenServ as infra-focused rather than TEE-or-decentralization-first, so no privacy mechanism is currently tagged for this record. Cost-reduction and accuracy-improvement claims (including the BRAID benchmark figures the project publishes) are recorded here as claims pending independent review, not adopted as fact.

API

Privacy

Scale

On-chain

Change log

• 2026-08-24 — record: seeded from provider roster v1.0 (Unverified) (source)
• 2026-09-14 — api.models: X claim (a_launch): Today, we open access to production-grade AI reasoning for every team. SERV Reasoning API is now live. (Claimed) (source)
• 2026-09-21 — api.models: X claim (a_launch): The 1st SERV Hackathon is live. Two weeks to build with SERV Reasoning and get rewarded. Get hands-on early before SERV v3/v4 brings graph sharding, self-improving intelligence, and task-specific models. Submissions close Sept 28. Pick your track: https://www.openserv.ai/hackathon (Claimed) (source)
• 2026-09-21 — record: X claim (f_funding): AI agents will manage trillions in capital across financial markets. Join the Spaces on Sep 22 with OpenServ Founder & CEO @open_founder and @IxsFinance CEO @julian2kwan, to explore what developers can build with SERV - across RWAs, tokenized stocks, automated trading, and more. As AI takes on increasingly complex financial decisions, managing real capital at scale requires better decision-making. With SERV Reasoning, developers will finally be able to build smarter, more reliable agents. Build the future of agentic finance today, and join the 1st SERV Hackathon: https://t.co/QphkmsaqUr (Claimed) (source)
• 2026-10-05 — api.models: X claim (a_launch): Give builders SERV Reasoning and let them cook. Onchain trading agents, AI fund managers, autonomous wallets, RWA risk, programmable payments, treasury management, gaming and more. SERV Hackathon winners announced next week. (Claimed) (source)
• 2026-10-12 — api.status: X claim (b_status): We’re building SERV to become core infrastructure for Enterprise AI. Our early work with Neol gave us a major advantage in building toward our vision. We had the opportunity to develop SERV against live production workloads across companies and governments, including the UAE government, while establishing a growing footprint across the Middle East. That meant access to real-world data and learnings that no theoretical framework or whitepaper could provide. These learnings shaped v1 and v2 of SERV Reasoning, moving our technology from a theoretical framework to a real-world use case, which now feeds directly into SERV v3 and Graph Sharding, the next stage of the reasoning engine. Neol runs network intelligence for governments and institutions, where agents surface real people for high-stakes decisions. In these environments, “usually right” isn’t good enough. The reasoning needs to be reliable, reproducible, and auditable. On one of Neol’s production agents, the same evaluation was run 2,400 times: - Prompt-engineered stack: 54.1% reliability - SERV research applied directly: 63.1% - Full SERV Reasoning methodology: 100% across every category SERV moved the workload from open-ended reasoning into structured decision graphs, then applied learnings from production, including subgraph decomposition and binary judgments, to make the reasoning more deterministic and testable. Higher reliability was only one part of the result. Neol gained an inspectable reasoning structure where results can be traced back to specific decisions, making the system easier to test, improve, and defend when challenged. Our vision is to make SERV the reasoning layer enterprises and institutions rely on to run AI at scale. Neol is an early proof point of this journey. (Claimed) (source)

The change log is append-only: corrections are recorded as new entries, never rewrites. Full feed via /api/v1/changes.

Sources

1. [roster] docs/decentralized-inference-provider-roster.md (2026-08-24)
2. [website] https://openserv.ai (2026-08-24)
3. [x-account] https://x.com/openservai (2026-08-24)