Automation that survives contact with real work.
Most AI pilots die somewhere between the demo and production. We build the unglamorous parts that decide whether an agent is useful on a Tuesday afternoon: the error handling, the audit trail, the human review step.
A demo is not a system.
It is easy to show an AI reading an invoice. It is much harder to handle the invoice that arrives as a photograph of a fax, in the wrong currency, referencing a policy number that does not exist in your system yet.
Real operations are made of exceptions. An automation that handles the clean 80% and quietly mangles the rest costs more than it saves, because now somebody has to check all of it.
So we build for the exceptions first: what happens when the model is unsure, who reviews it, what gets logged, and how a person takes over without starting the work again from scratch.
A batch of 240 documents. The agent scores how sure it is about each one, and the bars run from most sure to least. Drag the line to set where the cut falls.
142
98
of 240 documents
The same document, ten thousand times over.
- 01Intake: one document type, arriving at volume, every day
- 02Extract: every field arrives with a confidence score attached
- 03Route: above the line it files itself; below it, a person looks
High volume · low variance
Narrow first, then widen.
The fastest way to waste a year is to try to automate everything at once.
- 01
Find the volume
We look for the task your team repeats hundreds of times a month with the least judgement involved. That is where the result shows up first, and where it is easiest to prove.
- 02
Build the loop
A working pipeline on your real data, including the failure paths, in front of your team within weeks.
- 03
Measure honestly
Throughput, error rate, and how often a human had to step in. If the numbers do not move, we will tell you.
- 04
Widen
Once one loop is trusted and boring, the next one is far easier to justify, and much cheaper to build.
Where automation changes the outcome.
Not a menu of AI features. These are the patterns that hold up once the volume is real.
- 01
Document extraction and classification
Invoices, claims, contracts, medical reports. Structured output with confidence thresholds, so anything uncertain routes to a person for a decision.
- 02
Search across your own material
Answers grounded in your documents, with citations back to the source. When there is no supporting passage, it says so.
- 03
Workflow agents
Multi-step work: read, look up, decide, draft, file. A full trace of what was done and why, and an approval gate wherever being wrong is expensive.
- 04
Drafting and correspondence
First drafts of the letters, reports and summaries your team writes from the same facts every day. A person still reads and signs them.
- 05
Human-in-the-loop review
Queues, confidence scoring and one-click correction. Corrections feed back into the pipeline as training signal, the same day somebody makes them.
- 06
Integration into what you already run
Email, WhatsApp, your ERP, your document store. Automation that lives where people already work is automation they keep using.