Rayify provides decision intelligence systems for financial services, using specialist AI agents to adversarially test investment theseshare, validate claims, and monitor assumptions as conditions change. These agents—covering macro, regulatory, geopolitical, sector, and supply-chain lenses—generate principal-ready decision briefs that surface structured disagreement and identify what would change a decision. The platform integrates via a Python SDK, MCP server, and LangChain, and can be deployed on a client's own infrastructure using major AI modelsand trained on proprietary data.
Funding
Funding not disclosed
Founders
Product
Problem
Investment and strategy teams at family offices, institutional allocators, private equity, and venture capital firms face high-stakes decisions where being wrong is extremely costly. Traditional due diligence and research processes often rely on static reports and unstructured information, making it difficult to systematically stress-test theses, verify every claim, and continuously monitor whether the assumptions behind key positions still hold as markets, regulations, and geopolitics shift.
Solution
Rayify builds decision intelligence systems for financial services that use specialist AI agents to adversarially test investment theses. These agents, which can run on any major model and on a client's own infrastructure, ingest and cite real sources to challenge the reasoning behind a thesis from multiple perspectives, including macro, regulatory, geopolitical, sector, and supply-chain lenses. The platform surfaces structured disagreement, identifying where credible views converge, diverge, and break down, and then synthesizes the findings into a principal-ready decision brief that lays out the strongest case both ways exceptional and what assumptions are doing the most work. After a decision is made, Rayify continues to monitor those critical assumptions, alerting teams when conditions change and a thesis may need to be revisited. The system is trained on proprietary client data and includes auditable source lineage for every claim.
Target Audience
Primary customers are investment and strategy teams at family offices, institutional allocators, private equity firms, venture capital firms, and asset managers who need to stress-test complex, high-exposure decisions and monitor them over time.
Features
- Specialist AI agents with distinct lenses: macro, regulatory, geopolitical, sector, and supply-chain
- Adversarial thesis testing that surfaces structured disagreement and surfaces where credible views converge, diverge, and break down
- Continuous assumption monitoring after a decision is made, so teams learn when conditions shift
- Principal-ready decision briefs that include the strongest case both ways, the key assumptions doing the work, and what would change the team's mind
- Auditable source lineage for every claim made by the agents
- Deployment flexibility: runs on any major AI model, on the client's own infrastructure, trained on proprietary data
- Open API, Python SDK, MCP server, and LangChain integration for embedding into existing workflows