
Emett is a privacy-safe GTM intelligence platform that turns public web signals into verified, account-level briefs. It monitors sources like developer communities, competitor discussions, GitHub, Reddit, Hacker News, and public web pages to detect early signs of customer pain before they appear in traditional sales tools. Using Bright Data for live web access, LangChain for agent orchestration, AI/ML API for extraction and reasoning, Firebase for real-time updates, and Cognee for persistent account memory, Emett converts scattered signals into structured intelligence: detected pain, source context, confidence score, why-now reasoning, and recommended GTM action. Unlike invasive lead-scraping tools, Emett does not deanonymize individual users. It focuses on account-level insights and human-reviewed outreach guidance, helping sales and growth teams act earlier with more context, evidence, and trust.
31 May 2026

Developers waste countless hours trying to replicate production bugs, while project managers lack real-time visibility into codebase health. Worse, developers hesitate to let AI directly edit production code without mathematical proof that the fix actually works. BuildCheck AI solves this by transforming IBM Bob from a standard chat assistant into an autonomous, enterprise-grade DevSecOps pipeline. We help software teams turn ideas into impact faster by creating a mathematical trust layer between the AI and the developer. Our architecture consists of three core pillars: The Developer Interface (IBM Bob): We don't force developers to use a new website. We integrated our system directly into the IBM Bob IDE using Custom Modes, Slash Commands (/fixbug), and Context Mentions. The Execution Engine (Python MCP Server): This is the magic of our project. We built a custom Model Context Protocol (MCP) server that gives IBM Bob "hands." Instead of just guessing code, Bob executes a strict Test-Driven Development (TDD) loop in an isolated Python sandbox. The Command Center (Django & HTMX): A live web dashboard for product managers. As Bob autonomously fixes bugs in the IDE, or as our background security daemon blocks active server threats, the dashboard updates from RED to GREEN in real-time. In our demo, we tackle a complex Senior-level Fintech bug: a "penny shaving" proration error in an invoice calculator. When a messy bug report is received, a developer simply triggers our custom IBM Bob mode. Bob reads the report, autonomously writes a failing pytest to prove the missing penny, executes the test via the MCP Sandbox, fixes the algorithmic logic, and runs the test again to verify the math is perfect. Finally, Bob automatically hits our Django webhook to close the ticket. BuildCheck AI proves that with IBM Bob and MCP, AI doesn't just guess at code—it proves it works, securely and autonomously.
17 May 2026