SERV Reasoning
The AI engine you can
trust to run your business
SERV Reasoning sits between your agents and the frontier models they run on, and turns raw model output into execution your organization can stand behind.
Takes 2 minutes to apply · no credit card
Published research · arxiv 2512.15959
Open benchmarks · all logs public
In production · Neol, 6 months in a government deployment
Every team using AI hits the same wall.
The model was never the problem. Something else is missing between the model and your systems.
How does SERV solves this?
It stays inside the lines
Every task runs against a defined plan, with boundaries enforced by the engine rather than suggested in a prompt.
Numbers don't lie.
19,500 LLM calls across three public benchmarks, methodology and raw logs open for your own team to inspect.
0
0
LLM calls in the published evaluation
+0.0 pts
+0.0 pts
accuracy gain on multi-step reasoning
0x
0x
peak performance-per-dollar
🌍 Quality vs. Cost · same models, with and without the engine
These numbers come from public benchmarks.
Apply, and run the same comparison on your own workload.
It only takes 2 minutes to switch
Switching is an afternoon, not a quarter
If your agents call an OpenAI-compatible API, pointing them at SERV Reasoning is two lines of configuration. The highlighted lines are the entire change.
client = OpenAI(
base_url="https://api.openserv.ai/v1",
api_key=os.environ["OPENSERV_KEY"],
)
Ready to get clearer on what matters?
One decision. Made clearly. That’s all it takes.
What your team will ask.
How long does integration take?
Most teams swap the endpoint in under 20 minutes. Two lines of config; your agent loop, tools, and prompts stay as they are.
What does it add to latency?
Roughly 200-400ms on the first call of a multi-step task, neutral or faster after that. Sub-200ms real-time use isn't the right fit yet.
Which models are supported?
All major frontier models: OpenAI, Anthropic, Google, DeepSeek, xAI. Bring your own preference; the engine works within it.
Are my prompts used to train any model?
No, and we don't keep that option open for ourselves. Your prompts and outputs are not in any training pipeline, ours or anyone else's.
How long do you keep my run data?
30 days by default, zero-retention available on request and configured before your first call. Mention it on the application.