Blog

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Strategy

Why Most AI Pilots Fail (And What Actually Works)

Most AI pilots stall due to misaligned success criteria, shallow data integration, and missing feedback loops. Here’s what works instead.

Customer Support

Shelfware chatbots don’t solve L3 problems or reduce recontact rates. Teams need controllable systems, not generic copilots.

Search-native models change how agents retrieve, ground, and verify information in real time.

Product Insights

Conversation intelligence surfaces broken journeys, hidden feature demand, and the real reasons customers churn.

Engineering

We compare tool-calling across models inside a Swarm-style architecture, detailing routing, handoffs, and failure modes.

Customer Support

Support can be a data refinery: converting conversations into product insights, revenue signals, and risk detection.

Postmortems

When agents hit production, the real challenges are data quality, evaluation coverage, and human overrides.

Voice

Voice-native agents are finally viable: latency, interruptibility, and integration depth are crossing the threshold.

Launch

We launched BotDojo with a focus on evaluations and synthetic data for faster, safer iteration.