Your AI engineering partner.
Agentic systems, retrieval and automation, built with evaluation and cost control from the first week.
Most AI projects do not fail on the model. They fail on data access, retrieval quality, or a cost curve nobody modelled before launch.
We build the evaluation set before the feature, so accuracy is a number you can track from week one, and we ship with tracing and cost reporting attached — not added after the first invoice surprises someone.
What you get
- Feasibility assessment on your own data
- Graded evaluation set wired into CI
- Production pipeline with tracing and cost reporting
- Runbook for drift, regression and rollback
What we help with.
Agentic AI systems
Agents that call your tools and APIs, with guardrails, human approval steps and a trace behind every action.
AI automation
Document, support and back-office workflows automated end to end, with a measured hand-off to a person when confidence drops.
AI product development
Copilots, assistants and AI features designed and shipped as part of your product rather than bolted onto the side of it.
Retrieval and RAG
Chunking, embeddings, hybrid search and reranking tuned against your own corpus until retrieval stops being the bottleneck.
AI evaluation
A graded evaluation set wired into CI, so a prompt or model change is a number you can defend rather than a demo that felt better.
AI observability
Tracing, token accounting and quality monitoring on every production call, with alerts on drift, latency and regressions.
AI cost optimisation
Model routing, caching, batching and right-sized context, measured against a cost-per-request budget you set.
On-premise and private AI
Open-weight models running inside your VPC or data centre, for teams whose data is not allowed to leave the building.
Why choose Covaratech for ai engineering.
One team, start to finish
One team owns your system from architecture to on-call. There is no handover wall to throw requirements over.
Evidence before launch
AI features get an evaluation set before they get a launch date. If we cannot measure it, we say so.
Built to be handed over
Documentation and knowledge transfer are contract terms, not favours. You should be able to leave us at any point.
Senior engineers, not a bench
The people who scope your engagement are the ones who build and run it, never handed off to someone you haven't met.
Need help with ai engineering?
Agentic systems, retrieval and automation, built with evaluation and cost control from the first week.
Talk to usQuestions about ai engineering.
What comes up on the first call, with the answers we give on it.
1.How do you know an AI feature is actually working?
We build a graded evaluation set before the feature ships, wired into CI, so a prompt or model change is a number you can defend rather than a demo that felt better. That evaluation set is one of the deliverables, not an afterthought.
2.What stops AI costs from surprising us after launch?
Tracing and cost reporting ship with the production pipeline from day one, not after the first invoice surprises someone. On top of that, we tune model routing, caching, batching and context size against a cost-per-request budget you set.
3.Can this run on our own infrastructure, or does data have to leave?
Both are on the table. For teams whose data cannot leave the building, we run open-weight models inside your VPC or data centre. Either way, engagements start with a feasibility assessment against your own data before anything is built.
4.What happens if a model or prompt regresses after launch?
Every engagement ships with a runbook for drift, regression and rollback, backed by tracing and quality monitoring with alerts on drift, latency and regressions — so a regression is caught before a customer reports it.
5.Do you build autonomous agents, or just chat features?
Both. Agentic systems that call your tools and APIs with guardrails, human approval steps and a trace behind every action, alongside retrieval, document and back-office automation, and copilots shipped as part of your product.