Enterprise Context Orchestration

Enterprise AI fails
without context.

DeepGraph unifies enterprise data silos into a single AI-powered context engine, deployed entirely inside your perimeter. No data leaves, yet your agents can still reach external models when needed.

Every model reasons from truth.

See how it works →

Four hard truths nobody tells you about enterprise AI.

AI models are trained on the world. They are blind to your business.

The most expensive token is the one that didn't need to be sent.

Your AI reasons from a snapshot. Your business moves in real time.

Your security perimeter ends where your AI vendor's cloud begins.

The Core Problem

The AI Sees Everything, Understands Nothing.

"The signals are there and the data exists, but the AI still cannot connect the dots because the information lives in disconnected systems."

A pattern repeating at every bank, hospital, and enterprise — right now.

ERP handles transactions, SIEM captures events, and fraud systems detect patterns, but none see the full thread, so AI reasons from fragments and produces confidently wrong answers.

This is the context gap. DeepGraph closes it.

01

Fragmented enterprise knowledge

Every system holds a fragment. AI sees each silo in isolation and reasons from dangerously incomplete inputs.

02

Millions in integration tax

RAG surfaces fragments. GraphRAG requires domain-by-domain custom builds that take six to twelve months per use case. Complexity multiplies, while accuracy does not.

03

No sovereign deployment path

Every managed context cloud sends data outside your walls. Healthcare, finance, defense can't accept that trade-off.

Five Structural Advantages

What each one costs you
when you don't have it.

These aren't features. They are five architectural decisions competitors cannot retrofit, and enterprise AI cannot succeed without them.

$0 ROI

Several months of AI investment without right context results in no business impact

Full-Stack Context Intelligence

Context means more than data. It means meaning, relationships, and time.

DeepGraph manages three dimensions of context that RAG ignores entirely: semantic meaning (what entities are and how they relate), temporal lineage (how things changed and when), and reasoning chains (the causal path of evidence behind every AI output, so decisions are explainable, not just fast). Agents stop doing plumbing and start doing business logic. Inference is faster. Accuracy is compounding.

→ Agents focus on innovation, not integration

5× — 25×

token cost explosion makes agentic architectures economically fragile at scale

AI Optimizer · B2A Tokenomics

The first platform designed for the economics of the Business-to-Agent world.

Token costs are the hidden tax destroying agentic AI ROI. DeepGraph's AI-powered query optimizer doesn't just surface context; it does so by personalizing what gets surfaced, eliminating irrelevant tokens before they ever reach the model. Learning from every query, it dynamically weighs semantics, relationships, and exact matches within a single unified execution plan to deliver the right context in the fewest tokens. Best unit tokenomics in the industry. The optimizer compounds: it gets smarter with every query, reducing token spend continuously over time.

→ Best unit economics for agentic AI at enterprise scale

$4M — $10M

Average cost of a data breach when context, models, and data leave your control

Zero Egress · Sovereign Deployment

Your data, models, and context never leave your environment.

DeepGraph is the only platform built on a model-to-data architecture, where compute goes to context, not the other way around. For regulated industries, this is not a preference. It is a procurement requirement. Property-level encryption, RBAC and ReBAC access controls, cryptographic erasure, and immutable audit logs are built into the storage layer from day one, forming the architectural foundation that regulated industries require before compliance certifications are even pursued. Zero hardening cycles. Zero egress risk.

→ Required by financial services, healthcare, and defense

Stale ≠ Safe

stale context produces confidently wrong AI answers at the worst possible moments

Real-Time Signal Stitching

New enterprise signals are stitched into context the moment they arrive.

Most context platforms snapshot your data at ingestion and call it done. DeepGraph's streaming architecture means your context graph is continuously updated in real time, with every new transaction, event, clinical reading, or network telemetry is immediately stitched into the unified context. AI models always reason from the freshest possible state. No batch windows. No staleness. No decisions made on data that's 4 hours old.

→ Always-fresh context at inference speed

180+ days

lost to data purgatory, as engineers spend months mapping rigid schemas and silos. The schema tax leaves brittle agents that break as data evolves.

Intelligent Model-Based Ingestion

DeepGraph learns the shape of your data. You never have to define it.

Traditional data platforms require you to define schemas, map ontologies, and build connectors before ingestion begins. DeepGraph's learning ingestors are model-driven and study the structure, semantics, and relationships inside your enterprise data silos. The context graph is built from what your data actually says, not what a schema template assumes. Zero manual mapping for enterprise databases. Zero signal loss. A system that becomes more personalized to your enterprise with every ingestion cycle, not less.

→ Schema-free · Drift-aware · Learns your enterprise continuously

How It Works

One engine. Every source. Contextual intelligence.

DeepGraph sits between your enterprise data and your AI models, instantly transforming fragmented signals into contextual intelligence your agents can reason from,
out of the box.

01

Ingest & Unify

Learning ingestors connect all enterprise data sources into a unified context layer. Schema-free, drift-aware, no manual mapping. Any existing vector and graph database migrates seamlessly.

Intelligent ingestors · Continuous streaming

02

Orchestrate with AI

The AI-powered query optimizer understands intent and dynamically weighs semantics, relationships, and exact matches within a single unified execution plan. DeepGraph continuously enriches and deepens context using embedded models as it learns your enterprise with every interaction.

AI optimizer · Embedded model execution

03

Deliver at Speed

Sub-200ms context delivery to any AI model, agent, or application inside your perimeter. Always fresh, with full bi-temporal history and a complete audit trail for every output.

<200ms · Full audit trail

04

Enterprise Ready

Horizontal scaling, active-passive HA failover, and atomic point-in-time restore are built into the storage layer. RBAC and ReBAC access controls, property-level encryption, and immutable audit logs apply to every operation. Enterprise-grade from the ground up.

HA failover · Enterprise-grade security

Built For

Enterprise AI where context has consequences.

Built for industries where a wrong AI answer is not an inconvenience, but a fraud event, a missed diagnosis, or a compromised network.

Fraud detection, AML, and credit AI that reasons across your entire operation.

Unify core banking, fraud ledger, partner APIs, and compliance data. AI detects coordinated fraud in real time, before settlement, not after forensics.

  • Coordinated fraud detection across 3+ source systems simultaneously
  • AML pattern recognition across counterparty networks and histories
  • Zero-egress inside your regulated data environment
  • Full audit trail on every AI recommendation for examiner review

Without DeepGraph

API probe May 23. Wire transfer Jun 3. Ohio login Jun 9. Three systems. Three signals. Zero shared context. $2.3M transferred while it took 4 days of manual tracing by analysts for forensic review.

With DeepGraph

Context graph connects probe → wire → login on the same account across silos on Day 1. Classic multi-vector attack pattern visible in real time. Wire flagged before settlement. $2.3M saved.

Get Started

Your AI Is Missing Context.

Join the companies deploying DeepGraph to make AI deliver.