AI Company Evaluator

The Problem In Venture Capital, Private Equity, and Corporate M&A, initial company screening and triage (Enhanced Due Diligence) typically takes an analyst anywhere from 1 to 4 hours per case, while reading through dense financial filings and industry reports to build a baseline comprehension can consume a full day (8+ hours) before formal analysis even begins. This manual research process is slow, biased, and expensive. Our Solution We built an evaluation system of 6 parallelized AI agents that compresses this grueling, multi-hour workflow into under 60 seconds. When a user searches for a company, our system deploys a Gatekeeper to validate the entity, followed by a concurrent evaluation: News Agent: Scans for recent breaking news and catalysts. Competitor Agent: Maps the competitive landscape and moats. Business Model Agent: Evaluates pricing and unit economics. Risk Agent: Identifies downside vectors and impact scores. Opportunity Agent: Surfaces growth catalysts. Verdict Agent: Synthesizes the findings into a final, scored recommendation (Invest / Partner / Watch / Avoid). We also built a deterministic Evidence Engine that mathematically scores sources (Tier 1 vs. Tier 4) to prevent hallucination, alongside a Context-Aware Memory Chat that can autonomously launch fresh web searches if asked about new topics. ⚡ Use of AMD Platforms Because our multi-agent architecture relies on firing 5 to 6 LLM queries simultaneously alongside live search API calls, ultra-low latency is mandatory. To solve this, we integrated the Fireworks AI API, running Qwen 3.7+ directly on AMD Instinct™ MI300X accelerators. This AMD-powered hardware infrastructure provides the massive throughput required to run our parallel routing logic concurrently. Without the speed of the AMD MI300X accelerators, sequential reasoning would leave the user waiting minutes; instead, the entire evaluation pipeline streams and completes its synthesis in roughly 45 seconds.