A configurable AI gateway that plugs language models into real business data.
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What it is
Nexus is the AI backbone that sits between business systems — support desks, document stores, databases — and the language models that reason over them. It handles the unglamorous-but-essential parts: keeping each customer's data walled off from every other, remembering conversations, assembling the right context on the fly, and routing each request to the right model.
Why it exists
Every product that wants an AI feature ends up rebuilding the same plumbing: authentication, tenant isolation, data connectors, conversation memory. Nexus centralizes that layer once so new apps can ship AI features in days instead of months — without reinventing the foundations each time.
Who it's for
Internal products that need an AI brain, plus teams that want to embed configurable AI agents without building infrastructure from scratch.
What it does
- Multi-tenant gateway with strict per-customer data isolation
- Tool-using agent loop — the model can fetch live data on demand
- Streaming chat with persistent conversation memory
- Smart model routing: simple questions go to cheaper models, hard ones to stronger ones
- Provider-agnostic — swap between model vendors per app
- Admin console with a playground, knowledge base, and cost analytics
How it works
What made it interesting to build
The biggest turning point was moving from hard-coded behavior to a fully configurable system. Early versions baked every tool and setting into the code, so each new integration meant a fresh deploy. We rebuilt the core so behavior lives in configuration that admins can change without shipping code — a far bigger refactor than it sounds, because it touched how prompts, tools, and integrations were defined everywhere. Along the way we also learned to surface silent failures loudly: a retired model ID once broke chats quietly until we wired streaming errors into real logging.