Clean data. Cited. Confident. From every lease, loan, appraisal, and contract you own. Your AI roadmap is only as good as the data underneath it, and Kernel turns your documents into data your AI can actually use. Purpose-built for CRE, focused on nothing else.
Critical financial and operational data lives in PDFs and Word docs that are dense, cross-referential, and full of the kind of complexity that breaks every general approach. Amendment chains. Exhibits. Side letters. Definitions that span 200 pages. Kernel is built for exactly that complexity, with cross-document reasoning, full provenance, and confidence scores on every output.
Plug into the data layer via API. If your team is building AI products on top of your document corpus — copilots, agents, search, workflows — Kernel is the data foundation underneath. Clean, structured outputs from every doc type, with citations and confidence scores. Customer-defined schemas. Delivered via API or directly into your stack. Compresses the doc layer of your AI roadmap from quarters to weeks.
Use the tools we've built on it. If you want intelligence today without engineering, use Kernel's applications directly. Chat with your documents. Run agentic audits across your portfolio. Get findings with citations back to the source. Same data quality underneath as the API layer, accessible without a development team.
Bring Kernel into your existing stack. Single-tenant deployments, IaC-defined, with hard tenant isolation. Bring your own LLM (cloud-hosted or local). Customer-defined schemas, custom doc types, integration with your data warehouse or downstream systems. For firms with security, compliance, or scale requirements that need infrastructure-level partnership.
30 days to production data Hand us your priority doc types and a sample of your corpus. We stand up extraction against your real documents in 30 days. No system integration required to evaluate. Your team picks the accuracy benchmarks up front; you make the call at day 30.
SOC-2 Type II. Multi-tenant infrastructure with hard isolation enforced by architecture. Single-tenant deployments available. Zero third-party hosted dependencies. LLM-agnostic: use a model you host, or run a local one.
Modular pipeline with deterministic, cached, replayable stages. LLM bounded to the last mile. Each fact is its own retrieval-scoped, parallelizable job — adding new fact types doesn't reprocess your corpus, and a change to one fact never regresses another. Confidence scores on every output.
The layer underneath your AI Kernel doesn't replace what your team is building. We sit underneath the AI work your team is doing — on the part that's hardest and slowest to recreate internally — so your engineering hours go to the work that's differentiated to your firm. Copilots, agents, dashboards, workflows: yours. The document intelligence layer underneath them: ours.
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