InferEdge
InferEdge delivers agentic AI workflows for investment teams, automating research, portfolio management, risk, and distribution processes. The platform's agents pull filings and transcripts, update live financial models, and flag changes with source citations, processing roughly one million data points daily. Deployed with multi-billion-dollar funds, InferEdge embeds engineers within client environments and prices on agreed outcomes.
- AI Agents
- Artificial Intelligence
- Financial Technology
- Data & Analytics
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Investment teams spend days manually collating data from filings, transcripts, and guidance documents, then updating financial models and flagging changes against prior quarters. This manual process is slow, error-prone, and diverts analyst time away from higher-value work like thesis testing and decision-making.
Solution
InferEdge provides AI-as-a-service for investment teams, automating complete workflows across research, portfolio management, risk, and distribution. Agent-driven processes pull filings, transcripts, and guidance, update drivers in live models, and flag what changed since the last quarter. The platform processes roughly one million new data points per day and handles a document in under a minute. Outputs are evaluated, cited, and controlled from day one, making them suitable for production use. The system is scoped on a call, with a POC running in days and full delivery in weeks, priced on agreed outcomes.
Target Audience
Primary customers are investment teams at multi-billion-dollar funds, including research, portfolio management, risk, and distribution functions that need production-grade, cited AI outputs integrated into their existing workflows.
Features
- Agent harness that automates the full workflow: pulling filings, updating model drivers, and flagging changes against prior quarters
- Data pipelines processing ~1M new data points per day with sub-minute document processing
- Driver-level tracking with source citations (e.g., EBITDA margin, capex, net debt/EBITDA) tied to specific document pages and slides
- Workflow orchestration that sequences agent tasks and queues analyst and PM review steps (thesis testing, add/hold/trim/watch decisions)
- Portfolio contribution and attribution automation, reducing two days of manual collation across flows, revenue, and distribution costs
- Forward-deployed engineering with outcome-based pricing and output ownership retained by the client