AI that actually pays for itself

Generic AI gives generic answers. We connect AI to your documents and data so answers are accurate, grounded, and always come with sources.

• Answers from your documents, with sources

  We connect the AI to your manuals, policies, tickets, and databases, so every answer is grounded in your actual material and links to the paragraph it came from. That's what makes staff trust it, and what lets you audit it when someone disputes an answer.

• Always working from the latest version

  When a policy or price list is updated, the old version is replaced rather than left to compete with the new one. And because pure AI search reliably fumbles product codes and exact figures, we combine it with traditional search so both kinds of question get right answers.

• It only shows people what they may see

  The assistant respects your existing permissions: it will never reveal a document to someone who couldn't open it themselves. Without this, a knowledge assistant becomes the fastest route for a confidential file to reach the wrong employee.

• AI that takes actions: carefully

  For multi-step work, the AI gets a defined set of actions (look up an order, draft an email, raise a ticket), each one checked, logged, and reversible, with confirmation required before anything irreversible. Its independence is bounded by design, not by hope.

• Connects to your systems the standard way

  We use the emerging industry standard (MCP) for connecting AI to business systems, so new capabilities plug in cheaply and nothing is locked to one vendor's ecosystem.

• Custom training only when it pays

  Sometimes it's worth teaching a model your exact format, tone, or categories. Often it isn't, and we'll tell you honestly when a cheaper approach achieves the same result for nothing.

• Safe to write into your other systems

  Where AI output feeds your CRM or accounting system, every response is checked against strict rules and rejected if malformed. Nothing gets passed downstream on trust.

Your CRM, email, spreadsheets, and accounting finally talking to each other, so information flows without anyone retyping it.

• Automation you own (n8n)

  Automations hosted in your own systems, so sensitive records never pass through a third-party vendor, and there's no per-task pricing that punishes you for succeeding. Everything is saved and restorable like the rest of what we build.

• Quick wins with Make and Zapier

  For lightweight connections between mainstream tools, a hosted platform is live in hours and needs no maintenance. We're direct about the crossover point where its fees make a custom connection the cheaper long-run option.

• Custom connections where none exist

  Direct, resilient links to systems with no off-the-shelf connector, including legacy software and file-based exchanges, built so a duplicated message never creates a duplicated invoice.

• Triggered by anything, any time

  Work kicks off from a new email, an uploaded file, a form submission, or a schedule, with a queue that absorbs busy bursts, and a log of every run so you can prove afterwards what happened and why.

• Failures that alert a human

  Every automation has a defined failure path: retry, then alert a named owner, then park the item for review. Silent failure is how automation projects lose trust, so we design the unhappy path as carefully as the happy one.

• We fix the process before automating it

  We map the current process with the people who actually run it, and find the steps that should be deleted rather than automated. Automating a broken process just produces bad outcomes faster. This session frequently saves more time than the software does.

Your data stays yours. We design guardrails so AI is accurate, on-brand, and compliant, with humans in the loop where it counts.

• Your data never trains anyone's AI

  We use the enterprise arrangements where your inputs are contractually excluded from model training, document exactly who processes what, and support fully private setups where your policy requires. You get a written data-flow map suitable for a client's security review.

• Accuracy measured, not claimed

  Before launch we build a test from your real cases with known right answers, and report the score, not adjectives. That baseline then catches any decline in quality when something changes, which is the only way to improve an AI system safely.

• Tested against the worst case

  Before release we actively try to make the system fail at the thing that would hurt you most (inventing a price, giving regulated advice, leaking another customer's data) and build the protections those attempts reveal.

• A human approves the big calls

  For consequential decisions, AI drafts and a person approves, seeing the AI's confidence and its sources. We measure the approval rate, so you can see when a workflow has earned more independence, and pull it back when it hasn't.

• Ready for AI regulation

  Each use case classified by risk under the EU AI Act, the required records kept automatically, and people always told when they're talking to AI. Building this in during the project is far cheaper than retrofitting it under enforcement.

• Spending capped and visible

  AI costs tracked per workflow and per team, with budget alerts and hard caps so a runaway process can't produce a shocking invoice. We report cost per completed task next to the hours saved, so the return is measured rather than asserted.

• Every decision traceable

  Every AI-assisted decision keeps a record of what it saw, what it used, and what it answered. When a customer or regulator asks why a decision was made, the answer is retrievable rather than reconstructed.