Work we've built. Real problems, real outcomes.

Problem

The product team needed weekly competitor intelligence but had no resource dedicated to it. Research was ad-hoc, inconsistent, and often weeks out of date when it reached the team.

What we built

Built a research agent that monitors competitor sites, product pages, pricing, job postings and review sites on a weekly cycle. Synthesises changes into a structured brief with commentary on what changed, why it might matter, and what warrants a closer look.

Result

Consistent weekly competitive intelligence delivered without manual effort. Product team made two roadmap decisions based on signals surfaced by the agent in the first month.

Problem

The team received 50-80 documents per day across email and a shared drive. Staff spent 2 hours daily reading, classifying and routing each one manually. Backlogs built up. Documents occasionally went to the wrong team.

What we built

Built an agent that monitors the intake channels, reads each document, classifies by type and urgency, extracts key fields, and routes to the correct team queue with a structured summary. Edge cases flagged for human review.

Result

2 hours of daily manual work automated. Routing accuracy 97%. Human review queue reduced to an average of 6 items per day.

Problem

The ops team spent 4 hours every Monday manually pulling data from three sources to produce a weekly performance report. Same format every week. Error-prone.

What we built

Built an agent using Claude API with MCP data connectors that pulls from all three sources, applies consistent formatting logic, generates the report, and routes it to the right people automatically. Triggered every Monday at 7am.

Result

4 hours of manual work eliminated. Report lands in inboxes before anyone starts work. Zero formatting errors since deployment.