Problems we solve
The failures that stop an AI pilot becoming a product
A demo answers questions. A deployment has to prove where the answer came from, refuse when it has nothing, respect who is asking, and still be explicable two years later. Each page below takes one of those failures and shows what it takes to close it.
- AI document review automationPeople reading documents your software should be reading, at a volume that only grows.Cut a manual document review backlog by extracting structured fields from every file, each one cited back to the page it came from.
- Permission-aware AI retrievalYour assistant knows things this particular user is not allowed to see.Enforce document permissions inside retrieval, so restricted material is never fetched, never reaches the model, and never appears in an answer.
- Grounded AI answersIt answers confidently when it has nothing. Hallucination is a nuisance until it is in a legal memo.Stop confident, invented answers: tie every claim to a retrieved passage and make an empty scope refuse out loud instead of filling the gap.
- AI audit trailProve what your AI decided two years ago, with the evidence it decided on.Reproduce any past AI decision: the question, the documents in scope, the passages retrieved, the checks that ran, and the cited answer.
- AI agent accuracyRight most of the time, and nobody on the team knows how to move the number.Your agent is right 80% of the time and nobody can say why. Find the failing step by inspecting evidence per run instead of tuning prompts blind.
- Policy change sweepThe rule changed. Which of your forty thousand closed cases are now wrong?A rule changed. Find which past cases are now wrong by re-running them against the new policy, with the old and new evidence side by side.
- Prompt injection defenceA document your customer uploaded gave your agent new instructions.An uploaded document told your agent what to do. Treat document text as data rather than instructions, and keep tool use inside declared limits.
- Exhaustive document coverageTop-k cannot prove absence — and most agents claim it anyway.Top-k retrieval cannot prove absence. Understand why "there is no such clause" is unsupportable, and what an exhaustive pass has to do instead.
- Explainable AI decisionsThe person the decision is about has a right to know why.The person a decision is about can ask why. Produce an explanation from the same evidence the decision used, in language they can actually read.
- AI cost controlOne bad prompt should not be able to bankrupt you.Cap what any single run, case or deployment can spend, so one badly-shaped prompt cannot turn into a five-figure invoice overnight.
- Build vs buy vertical AINine months of plumbing before you ship the thing you actually sell.Nine months of retrieval, permissions, citations and audit plumbing before you ship a feature. What that build actually costs, itemised.
- Legacy archive OCRTwenty years of paper your AI cannot read a single word of.Twenty years of scans, faxes and handwriting your AI cannot read. Run OCR at ingestion so the archive becomes retrievable alongside everything else.
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