We've reimagined how financial professionals find their target markets. No filters to learn. No complex queries. Just ask what you need.
Traditional database interfaces force users to learn complex filter systems. We built something fundamentally different.
Three AI-powered systems work together to understand your intent and deliver precise results.
Ask questions in plain English. No filter syntax to learn.
GPT-4 interprets your intent and extracts precise parameters.
Vector embeddings find conceptually similar results.
Transparent filters, matched tags, and intelligent suggestions.
The same deep, validated data—now accessible to everyone, regardless of technical expertise.
What took 5-10 minutes of filter configuration now takes seconds. Your team spends less time searching, more time selling.
New team members are productive from day one. No training on filter systems, no memorizing data taxonomies. Just ask.
Semantic search finds companies by concept, not just keywords. "Distressed credit specialists" works without knowing exact tag names.
Refine searches conversationally. "Also include family offices" or "exclude funds under $500M" feels like talking to a colleague.
See exactly what filters were applied and which tags matched. Understand why results appeared—no black box.
Same security, same data quality, same accuracy. Chat is a new interface to the trusted HedgeID data you rely on.
This isn't a chatbot bolted onto a database. It's infrastructure for how financial data will be accessed.
The financial services industry is entering the AI agent era. When your team deploys AI assistants for research and prospecting, those agents need high-quality data sources.
HedgeID is positioning as that infrastructure layer—the knowledge base that powers AI workflows across the industry.
Any AI assistant (Claude, GPT, enterprise systems) can query HedgeID as a tool.
Our value is the data and semantic layer, not the specific LLM. We're future-proof.
Every tag we add, every company we classify makes the AI smarter. Data quality = AI quality.
100k+ firms with 120+ fields each. Years to replicate.
200+ tags with confidence scores and vector embeddings.
Publishing workflow, email validation, human-in-the-loop QA.
Service providers, org hierarchies, professional networks.
Chat is the foundation. Here's what it enables.
Save searches, get notified when new companies match
Direct export to HubSpot, Salesforce, CSV
Share chat searches with colleagues via Slack
"Compare these 5 funds side by side"
Multi-step autonomous research workflows
"How is this fund connected to that executive?"
Trend analysis and pattern recognition
Conversational search via mobile voice
Third-party AI products query HedgeID API
Proactive insights based on pattern recognition
From discovery to outreach in one conversation
The data layer that powers financial AI
Consistent narratives for customers, investors, and internal teams.
"HedgeID now lets you find funds and contacts by simply asking. No filters to learn, no complex searches—just ask what you need and get answers in seconds."
Start natural: "Hedge funds in the Northeast with over $5B AUM" — show how plain English works.
Show refinement: "Which ones focus on fixed income?" — demonstrate conversational flow.
Cross to contacts: "Show me the portfolio managers at these funds" — seamless entity switching.
Highlight transparency: "See exactly what filters were applied" — no black box, full control.
Show suggestions: "When results are empty, we help you adjust" — intelligent assistance.
"HedgeID has built the first AI-native financial data platform. While competitors bolt chatbots onto databases, we've reimagined data access for the AI era. Our semantic classification system—built over years—now powers intelligent search that understands what users mean, not just what they type."
First-mover advantage in AI-native financial data. Years of data quality work now becomes AI training data.
Data quality moat deepens with AI. Every tag, every classification makes the system smarter. Competitors can't shortcut this.
Platform architecture supports B2B2AI model. Our API can power third-party AI workflows across the industry.
Usage metrics demonstrate PMF: Time to result (5min → <5sec), queries per user, refinement patterns.
"We're not just a database company anymore—we're an AI company with a data advantage. Every data quality improvement now has dual value: human users AND AI accuracy."
System prompt optimization is product development. The prompt IS the product intelligence.
Embedding quality = search quality. Invest in tag coverage and vector accuracy.
Latency matters. 5 seconds is the new threshold. Every optimization counts.
Chat feedback informs roadmap. We now see exactly what users want to find.