Technology services
HARBAN AI LABS is building 8 service lines for teams that need evidence, not demos. Each is listed with its real status. Today every one of them is planned: we are designing them and not yet taking engagements.
Statuses change only when we can deliver the service.
When a service line’s status changes, the new status is published on that service’s page and on this index. We do not show client logos, testimonials or case studies because we do not have any yet — the evidence we can offer is our published work, linked below.
Practice
Task-specific evaluation suites and benchmark analysis that answer a concrete decision — which model to ship, whether a release regressed, where a system fails.
Structured adversarial testing of LLM applications and agents — prompt injection, unsafe tool use, data leakage and failure under stress.
Practice
Design and build of tool-using agents with explicit control flow, scoped permissions, evaluation and observability from day one.
Production LLM features and applications — from API integration and prompt design to structured outputs, testing and deployment.
Retrieval-augmented systems over your documents and data, measured on retrieval quality and answer faithfulness — not demos.
Automations that combine deterministic pipelines with model steps — document processing, classification, extraction and routing.
Time-boxed builds that answer one question — is this feasible, and how well does it work on your data?
Practice
Literature reviews, model and vendor assessments, experiment design and technical due diligence for AI initiatives.
Process
You describe the problem, the decision you need to make and any constraints — through the form on Work with us.
We talk through the system, the data and what success looks like, and decide together whether we are the right fit.
Scope, deliverables and acceptance criteria are written down and agreed before any work starts.
Work is measured against the agreed acceptance criteria as it progresses, with results you can inspect rather than demos.
Deliverables, documentation and the means to re-run the evaluations pass to your team, so the work can be checked without us.
This is the process we intend to follow. We do not publish project timelines or delivery service levels until we can commit to them; anything time-bound is agreed in the written proposal.
Evidence