LLMs and machine learning applied to actual business processes — document processing, support triage, content pipelines, search. Measured by hours saved and accuracy, not hype.
We score candidate workflows by volume, risk and hours saved.
A working prototype against your real data, with accuracy evals.
Guardrails, monitoring, cost controls — then rollout.
High-volume text work: documents, tickets, tagging, drafting, search. We scope by measurable hours saved — if the numbers are not there, we say so.
Retrieval grounding, structured outputs, automated evals and human review where stakes are high. Accuracy is engineered, not assumed.
Private deployments, redaction pipelines and strict data boundaries. Your data trains nothing and leaves nothing.
Bring one painful, high-volume workflow — we'll assess whether AI genuinely beats the status quo.