Frontier models → Launch
Any frontier model. POC to production, in days.
Claude, Gemini, OpenAI, open-weight models – more teams are building with all of them in-house. NayaOne is where those builds get proven, against synthetic data and real vendor APIs, inside the air-gap, and moved to launch with the evidence risk and security require.
“We had not yet started with AI. Inside a fortnight on NayaOne we had a Claude build proven on synthetic data and a clear path to production.”
CIO, Group Insurance
North American insurer
31
financial institutions testing frontier models on NayaOne today
9 days
median from prototype to production-ready evidence
Model-agnostic by design
Test any AI model or tool, side by side.
NayaOne is not tied to one vendor. Bring the models and tools your teams already use, evaluate them on identical synthetic data, and choose on evidence.
Claude
OpenAI
Gemini
Cursor
Mistral
Llama
Cohere
Copilot
What teams test here
One environment for every kind of AI question – whether the model is bought, hosted or built in-house.
Model bake-offs
Score competing frontier and open-weight models on identical prompts and identical synthetic data, with cost and latency captured alongside accuracy.
Agents and tool use
Let agents plan, call tools and act across systems, with every call observable, before they touch a production interface.
Retrieval and document work
Test RAG pipelines, extraction and summarisation on deliberately messy statements, forms and identity documents.
Guardrails and red-teaming
Run hallucination, jailbreak, bias and prompt-injection cases as part of the test set, not as an afterthought.
Build versus buy
Put an in-house build and a bought vendor solution on the same data in the same environment, and let evidence settle the argument.
Fine-tunes and self-hosting
Host open-weight models inside the boundary, compare tuned variants, and prove what runs on your own infrastructure.
The path to launch
Four steps. The same environment from first prompt to production handoff.
1
Prototype with your chosen models in the sandbox
Spin up an air-gapped workspace and build with any model – hosted or open-weight – against representative synthetic data, bank statements, documents, transactions, without exposing a single real record.
2
Bake models off against real APIs
Wire the build into 1,500+ pre-integrated APIs and run competing models on identical prompts and identical data. Measure accuracy, latency, cost and fit on evidence, not a demo.
3
Generate the evidence pack
Export a documented record for risk, security and compliance, what was tested, on what data, with what result. Governance happens early, not as a last-minute blocker.
4
Launch to production
Hand the proven build off, first into your own sandbox, then production. The work that took a quarter to even start is live in days.
In practice
Building with frontier models inside the air-gap, on real bank infrastructure.
A global bank’s wealth team used Claude on NayaOne-provisioned, air-gapped workspaces to build an interactive 3D visualisation of a client-journey ecosystem for an internal forum, with no dedicated development team and no corporate email required on the tooling.
Elsewhere, an insurer’s team built a working application with Claude Code and Cursor in a disconnected environment, then exposed it to pilot users, exactly the path from prompt to proof that production-grade governance demands.
Air-gapped, no corporate email needed
Sandbox accounts on provisioned VMs, isolated from the estate.
Your AI coding tools, ready on arrival
Claude Code, Cursor, Copilot, Gemini CLI and the rest, pre-installed.
Prompt to pilot users
Working apps exposed to beta users without production deployment.
Build in-house? Even better.
The sandbox is where build-vs-buy stops being a guess.
“I’m going to be doing less buying and more building in-house.” We hear it constantly, and it’s exactly why NayaOne exists. Prove the in-house build and the bought vendor on identical data, in the same environment, and let the evidence decide.
🛡 Air-gapped guardrails
Models and data stay inside the boundary, with entitlements per project.
📋 An audit trail by default
Every evaluation is documented, ready for the governance conversation.
⚡ Days, not delivery cycles
Pre-integrated infrastructure means you start at build, not setup.
The headline
A prototype on Friday can be production-bound evidence by the following week – whichever model you built it on.