AI-native investment platform
The operating system for AI-native investment funds
AINative Platform puts data, models and AI agents at the core of every investment decision — from discovery and screening to due diligence, committee and portfolio monitoring.
Positioning
AI-enabled vs. AI-native
Most investment software bolts AI onto existing tools. AINative Platform is built the other way around — AI is the foundation the entire workflow runs on.
AI-enabled software
AI improves individual tasks in an existing product; core workflows run independently of AI; data and models sit outside the core architecture.
AINative Platform
Data, models and agent orchestration form the core; AI connects research with team decisions; continuous learning across the full workflow.
Why now
Problems we solve
Problem
Discovery depends on the network — manual sourcing misses companies outside familiar contacts and events.
Platform response
Screen the full universe and surface early signals from revenue, hiring, grants and contracts.
Problem
Assessment takes too long — data collection and document preparation consume expert time.
Platform response
LLM agents support screening, document checks and memo drafts; experts retain decision authority.
Problem
Knowledge stays with individuals — research starts over; rationale and outcomes rarely feed the next decision.
Platform response
A shared evidence base captures decisions and outcomes, preserving institutional knowledge.
Problem
Early companies are hard to assess — sparse financial data makes promising teams hard to compare.
Platform response
Track research, grants, product signals and founder evidence to structure early-stage review.
Workflow
A repeatable screening funnel
Independent scoring
Gradient boosting with classical ML, LLM assessment, supervised models trained on expert labels.
Automated due diligence
17 dimensions across market, product, technology, financials and team; agent-built knowledge graph; cross-checks across evidence sources; company research summary.
Configurable focus
Rank by AI capability, then re-rank the same universe for any other technology segment.
Architecture
Five layers of platform architecture
A shared data foundation connects evidence with decisions.
Business workflows and UI
Explainable rankings, pipeline management, monitoring dashboards and portfolio support tools.
Orchestration and AI agents
Diligence agents and memo drafts with retrieval over current reports, documents and transcripts.
Models
Clustering, supervised scoring, ML predictors and LLM assessment with expert feedback.
Data processing and storage
Event-driven pipelines, ETL/ELT, normalization, knowledge graphs and a shared ontology.
Data sources
Public registries, research and grant databases, company directories, investor datasets and events.
Connected workflows
One intelligence layer across the research lifecycle
Shared data and models
Decisions and outcomes feed future research
Sectors
Four sectors in one configurable platform
Applied enterprise AI
Businesses turning AI into repeatable enterprise products.
Evidence
Commercial revenue, reference deployments, an engineering core.
Industrial software and robotics
Solutions that improve industrial operations.
Evidence
Site pilots, contracted revenue, integration requirements.
Cybersecurity and infrastructure
Product differentiation, technical readiness, enterprise adoption.
Evidence
Security certifications, customer concentration, deployment history.
Established B2B software
Operating history, contracts, measurable profitability.
Evidence
Financial statements, customer retention, recurring revenue.
Sector coverage is configured to each customer's technology thesis.
Configuration
A target profile tailored to each mandate
| Criterion | Example configuration |
|---|---|
| Technology focus | Differentiated technology aligned with your thesis |
| Stage | Seed+ to growth |
| Annual revenue | From a defined threshold |
| Revenue growth | Multi-year CAGR target |
| Addressable market | Scope and size defined per mandate |
| Product | Proprietary technology, dataset or defensible IP |
| Team | Committed founders with scaling experience |
| Transaction size and ownership | Customer-defined |
| Exit path | Strategic acquisition |
Roadmap
One workspace for discovery, diligence and ongoing monitoring
Discovery and screening
Continuously updated company universe; ML, LLM and supervised scoring; automated diligence across 17 dimensions; ranking tailored to each technology thesis.
Company assessment
Pre-meeting review of financials, market, product, IP and risks; technical due diligence; pitch deck analysis at scale; founder interview analysis; draft investment memos.
Transaction support
Term sheet drafts from templates; legal and tax risk review; valuation, ownership and dilution scenarios.
Ongoing monitoring
Reporting, litigation, hiring and news tracking; risk signals and plan-deviation alerts; rescoring the universe; strategic buyers and exit windows.
Engagement
Flexible ways to adopt the platform
Dedicated platform
- Dedicated deployment built on our production platform
- CTO-led implementation and workflow adoption
- Agreed software IP and operating responsibilities
- Customer sponsors the roadmap
SaaS subscription
- Pilot in a selected technology sector
- Shared production workspace and AI diligence
- Configurable screening criteria and data coverage
- Implementation and analyst onboarding
Joint product venture
- Co-develop a focused platform business
- Combine your domain expertise with our platform
- Agreed ownership, IP and governance
- Dedicated product and engineering team
Experts decide. AI does the groundwork.
Every ranking is explainable, every memo is a draft for expert review, and every decision feeds the shared evidence base.
Contact
Request a demo
Tell us about your fund and we will set up a walkthrough tailored to your workflow.