Four layers between fragmented data and AI.
Ingest, Harmonize, Enrich, Agentify. The layers are cumulative — each builds on the one beneath it. Engage at any depth; the full stack is where accuracy and defensibility compound.
Pick a layer. See it in your industry.
The same four layers run under every engagement. Select one to see exactly what it does for embedded finance, healthcare procurement and mortgage lending.
Pull from sources that were never meant to talk.
We build APIs, connectors, webhooks and file parsers to pull from fragmented sources — even systems with no API at all. The source changes nothing about how it operates; we connect to what it already runs.
How model accuracy goes from 60% to 96%.
A model handed raw, inconsistently labeled data hallucinates — the model isn’t deficient, the data isn’t prepared. Curation with structured human review on the edge cases is what closes the gap.
Standard LLM accuracy on raw, inconsistently labeled enterprise data.
Structured review on edge cases. Every resolved case sharpens the next.
You bring the domain. We bring the infrastructure.
Domain consultants deliver AI data services to their own clients on EMBD. You own Layer 4 — the agents and the relationship. We run Ingest, Harmonize and Enrich underneath.
Engage your client
You bring the domain expertise and the relationship. You know what decisions matter.
Layer —Scope the pipeline
Together we map the sources, the normalization and the AI-ready surfaces the use case needs.
Layer —Deploy with EMBD
We stand up Layers 1–3; you build and own the agents on top.
Layer 1–3 + yoursBlocked on data your AI can’t reach?
Start at any layer — ingestion, harmonization, the full live-state stack. For embedded finance, healthcare procurement, mortgage lending, or the next fragmented sector on your roadmap.