We build the systems your business runs on — with AI where it earns its place.
Anveth designs and builds backend infrastructure, real-time data systems, and internal tools — and integrates language models into them as working components, not demos.
About Anveth
Anveth is a small software studio. We build the software a business runs on but rarely shows to the outside world: data pipelines, services, dashboards, and the automation that ties them together.
Since 2025 much of that work has involved AI: putting language models behind real workflows, with proper evaluation, guardrails, and cost control. We work with each client from the first scoping conversation through long-term maintenance, with a bias toward systems that are reliable, observable, and built to last.
What we build
Two lines of work, one engineering standard.
AI integration & LLM applications
Retrieval over your own documents and data, structured extraction, classification, and copilots inside the tools your team already uses.
Agent workflows & automation
Multi-step processes that call your systems, check their own work, and hand off to a human when confidence is low.
AI enablement for engineering teams
Evaluation harnesses, prompt and model management, and coding-agent workflows so your own developers ship faster with less risk.
Real-time data systems
Ingestion, processing, and monitoring pipelines that stay up around the clock.
Backend & infrastructure
APIs, services, and the operational backbone that keeps them running — cloud or on-prem.
Dashboards & internal tools
Interfaces that turn raw systems into something a team can actually use every day.
How we approach AI
A model is a component with a failure rate. We engineer around that, the same way we would around any other unreliable dependency.
- Grounded in your dataAnswers cite the source they came from. If the source isn't there, the system says so instead of guessing.
- Measured, not vibesEvery feature ships with an evaluation set. We know the accuracy before you do, and we track it after launch.
- Human in the loop where it mattersLow-confidence and high-stakes actions route to a person. Automation earns autonomy gradually.
- Cost and latency budgetsModel choice, caching, and batching are design decisions. You get a per-request cost you can plan around.
- Your data stays yoursProvider APIs, private deployments, or open-weight models on your own hardware — chosen by your constraints, not ours.
- Swappable by designModels change every few months. We isolate them behind clean interfaces so upgrading is a config change, not a rewrite.
How we work
Map it first
We map the problem, the data, and the failure modes before writing a line of code.
Working increments
Small, working pieces you can see and steer as they ship.
Ready for load
Tested, observable, evaluated, and ready for real production traffic.
We stay on
Systems live longer than launches, so we don't disappear after one.
The toolkit
Boring where it should be boring. We pick tools your team can keep running without us.
Have a system to build, or one that needs AI in it?
Tell us what you're working on — we read everything that comes in and usually reply within a couple of days.