BGE-M3 Search
liveA self-hosted embeddings and semantic-search service with a dashboard and retrieval observability. The foundation of every RAG and knowledge search.
- latency
- <50ms
- search modes
- 3×
- deploy
- self-host
Most technology today adds noise. We subtract. We design agents, infrastructure and data systems that give back time, attention and agency — then get out of the way.
We don't build AI for its own sake. We build systems that do the work in the background — so people can return to what's human: to decisions, to family, to life beyond the screen.
Good technology is quiet. We measure it by how much attention it gives back, not how much it takes.
Local embeddings, PII masked before the cloud, the option to fully self-host the models, code ownership. We design so it can move to your hardware and you can switch providers — never the other way round.
Not a chatbot for small talk. Agents that do real work in real processes — and report the truth, not optimism.
We research on our own infrastructure, then deploy for clients. Click a domain to go deeper.
Not one framework — an arsenal. From LLM serving (vLLM, TensorRT-LLM) and agent graphs (LangGraph, MCP), through vector databases and data streams, to Rust, Kubernetes and CUDA. We command the whole layer and pick it for the problem, not the trend.
It starts with the user's question. PII is masked before anything leaves the box.
BGE-M3 computes 1024-dim vectors locally. Retrieval never leaves for the cloud — data stays put.
The router is the only entry to the models. It picks the cheapest tier that fits, throttles and logs.
The answer returns with source citations. If retrieval is too weak — escalate to a human, never hallucinate.
One closed loop, repeatable for every system. No fake-done, no optimism without proof.
We read the real state: repo, runtime, data.
We find the gap between intent and reality.
The smallest change with the most leverage.
Modular, observable, with a rollback.
Proof: a test, a log, a screenshot — not a claim.
Self-audit, regressions, and loop again.
Real systems running on our own infrastructure. The numbers refresh live from our API.
Track record (cumulative)
* live metrics from /v1/metrics · service status live →
"Technology worth building doesn't fight for your attention. It gives you back time — and gets out of the way, so you can live."
We start with an audit and a fixed, low-cost pilot — one process, a measurable result, usually in weeks, not a big contract. We show a working system before we ask for trust.