The pipeline you see on the home page runs on a full platform: ingestion, document and meeting intelligence, entity mastering, an agent layer, search, governed review, reporting and distribution. Ten capabilities, one system, from document to system of record.
Each of these is a capability a competitor sells as a whole product. ADI runs them as one system, with the same governed data flowing through every one.
Email, cloud drives, SFTP, document portals, FIX message logs and data-warehouse connectors, all flowing into a versioned store.
OCR, a classification taxonomy, schema-driven extraction into runtime-typed models, a self-service extraction wizard and zero-shot named-entity recognition with a feedback loop.
A staged transcript pipeline: entity and role association, pitch-field extraction with citations, insight, labeling, and a QA stage that validates every CRM writeback against source before commit.
Ensemble matching with adaptive confidence, graph clustering, and golden records tied to your source of truth, enriched from commercial reference universes like S&P Capital IQ, Preqin, Cherre and ICE, with public identifiers (LEI, FIGI) layered on where they exist.
A sandboxed code-generation agent over 37 audited finance tools; a multi-LLM chat layer; a visual Agent Builder; plain-language questions compiled to SQL; NL to dashboard; an MCP server for external AI clients.
Per-tenant vector collections, dual chunking strategies and a semantic catalog, five collections per vertical across assets, documents, summaries, entities and parties.
Maker-checker task queues with field-level edits, approve and reject, and a full audit trail, on an orchestrator with a scheduler, event router and autoscaler.
NL to SQL, drag-drop dashboards, charting and PDF export, holdings and ownership graphs, valuation and a query lab, plus RAG-driven branded Word and PDF report synthesis.
A distribution layer with governed reader accounts, table sharing and reporting-client provisioning, white-label data delivery on top of verified data.
Per-tenant isolation, role-based access by organization and department, secret management, configuration services and platform-wide observability.
A number is only as good as knowing which entity it belongs to. This is the layer aggregation tools skip, and the reason ADI's data can be acted on.
The agent is a commodity. Everything that makes an agent safe to act on financial data, typed schemas, identifier grounding, a human review gate and a writeback-QA stage, ADI already built. That is the layer the frontier vendors do not have.
Once every field is extracted, mastered and checked, two things come for free: a portfolio you can query in plain language, and reporting that builds itself from numbers you already trust. Questions compile to SQL and run against governed tables: the model writes the query, the database does the math, so answers are deterministic, auditable and cheap to run at volume.
Models change every quarter. ADI does not bet the platform on one.
Aggregation platforms are strong at the top of the stack: portals, categorization, extraction. Everything below that is where ADI separates: higher accuracy, end-to-end automation, deployment in your control, no managed-services layer, and a lower total cost.
A working session on your real documents and systems, across the capabilities your team needs most.