AI product
Beyond Market Intelligence keeps AI product in one place: 3 stories so far. The section currently leads with “Explore how Foresight AI helps reliability teams test and fix failures faster”, “Anthropic, Clay, and Gamma on moving AI from demo to deployment”, and “From counterfactual analysis to an AI product that empowers your data work”. Reliability teams have long relied on reactive troubleshooting, waiting for incidents to reveal weaknesses. The leap from AI demo to daily deployment is the hardest part of the journey. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every AI product story on Beyond Market Intelligence, newest first.
Explore how Foresight AI helps reliability teams test and fix failures faster
Reliability teams have long relied on reactive troubleshooting, waiting for incidents to reveal weaknesses. Gremlin's general availability of Foresight AI flips that model. It actively analyzes services for potential failures, recommends fixes, and then reruns tests to confirm the solution works. This agentic approach transforms testing from a manual burden into an automated cycle of discovery and correction. For those exploring how to keep complex systems stable, Foresight AI offers a practical path forward.
Anthropic, Clay, and Gamma on moving AI from demo to deployment
The leap from AI demo to daily deployment is the hardest part of the journey. At TechCrunch Disrupt 2026, Anthropic, Clay, and Gamma will share exactly what that transition demands. We expect real talk about friction, not just polished results. If you are serious about moving past the pilot phase, this session is worth your time. Register now and get 50% off a second pass. For more on Anthropic's latest advances, read our coverage of "Sonnet 5.5 delivers faster insights while reducing your token spend."
From counterfactual analysis to an AI product that empowers your data work
Building a counterfactual engine is one thing. Turning it into a multi-agent product is another. This walkthrough shows exactly what it takes to move interrupted time series analysis from a manual research task into an AI-driven workflow. It's a practical, honest look at the engineering and design choices that matter. If you're curious how structured reasoning gets automated, this is worth your time. For a deeper dive into the underlying mechanics, our guide to distributed algorithms pairs well with the concepts explored here.