What we build with it
Assistants that answer questions from your own documents and show the passage they took the answer from. Extraction that turns invoices, contracts and emails into clean records. Triage that reads every incoming request and hands it to the right person with a draft reply attached. Agents that carry a task through several systems and stop to ask when they aren't sure.
It all runs inside the tools your team already uses, rather than in one more app somebody has to remember to open.
Where a model earns its place
Language models are very good at a specific shape of problem: input that is messy, varied and written by humans, where the rules are real but there are hundreds of them and they all have exceptions. Classifying free-text notes, pulling structured fields out of documents that were never designed to be parsed, summarizing a queue nobody has time to read.
Those are the jobs where writing the logic by hand means writing it forever, because every new input finds a case you didn't think of.
Models for judgment, code for rules
The AI systems that hold up use both. A model reads the messy input and makes the judgment call; ordinary code does the arithmetic, the validation and the routing on known fields, where there's a right answer and a test can prove it. Getting that split right is most of what makes an AI feature reliable.
We learned it the long way around: writing language technology by hand to catch grammar mistakes for Microsoft, and preparing the data machine learning systems run on. That's how we know where a model earns its keep, and where a few lines of code will do it better.
Built so you can check it
Anything a model decides gets logged with what it saw and what it produced, so a wrong answer is something you can go and look at rather than something you argue about. Where the cost of being wrong is high, a person confirms before anything is committed.
We'll also tell you what it costs to run, per document or per month, before you commit to it. That number decides more projects than the technology does.