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The Context OS for Agentic Intelligence

Book Executive Demo

The Operating System Between Data and Decisions

Context OS is the infrastructure layer that compiles enterprise context, enforces governance structurally, and produces evidence at every decision. It doesn't hope agents behave — it makes non-compliance architecturally impossible

4 wksDeployment
60%Cost reduction
100%Decision traceability

Enterprise AI Has Execution Infrastructure. It Doesn't Have a Control Layer

Most enterprises invest in compute, models, and agent frameworks, yet a structural gap remains between data and agent execution—no system compiles context, enforces authority, or produces evidence—so agents act without proving correctness

Context Gap

No Shared Context

Agents operate independently, lacking unified understanding or awareness

Each agent isolated

No shared reality

Conflicting decisions possible

Temporal tracking missing

Knowledge not centralized

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Outcome: AI actions lack coordinated understanding across the enterprise

Weak Enforcement

Policies Suggestions

Policy enforcement exists as optional prompts rather than structural rules

Prompts over rules

Guardrails may fail

No automatic compliance

Behavioral guidance only

Enforcement inconsistent

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Outcome: Agents may act contrary to policy without structural safeguards

Evidence Missing

Compliance Blind

Decisions produce no inherent audit trail or evidence of correctness

Post-hoc audits only

No real-time proof

Compliance gaps persist

Decisions unverifiable

Risk unmanaged

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Outcome: Enterprises cannot prove AI decisions were correct

Three Planes. One Operating System

Context OS operates as three interconnected planes that sit between your systems of record and agent execution layer

Context Plane

What AI knows — entities, relationships, temporal state, rules, provenance, and SOPs compiled into a queryable Context Graph

Entity resolution Temporal state Provenance tracking Conflict resolution

Control Plane

What AI is allowed to do — policy gates, authority models, threshold rules, and decision boundaries compiled into the execution path

Policy Gates Authority models Threshold rules Escalation paths

Decision Plane

Why it happened — every decision produces a trace recording context consumed, policy evaluated, authority verified, and outcome generated

Decision Traces Precedent search Decision replay Audit packs

What Context OS Delivers

Context OS enforces policies, tracks decisions, and provides contextual intelligence, ensuring agents act compliantly and traceably

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Structural Enforcement

Policy is compiled into the decision path — not bolted on as prompts. Non-compliant outputs are removed from the possibility space. The model doesn't refuse; it structurally cannot

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Continuous Learning Loop

Every decision trace feeds back into the Context Graph. Agents don't start cold — they inherit the full reasoning history of every prior decision

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Context Graph

A temporal, multi-modal knowledge graph that connects entities, rules, SOPs, and provenance across all enterprise data. Causal understanding, not just correlations

decision-ledger

Decision Ledger

An immutable record of every decision: what context was consumed, what policy was evaluated, what authority was verified, and what evidence was produced

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Agent Registry

Central inventory of every agent — what it accesses, what it's authorized to do, its decision history, and its current scope. RBAC for machines

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Governance as a Gradient

Governance scales with risk. Low-risk actions auto-approve. Medium-risk decisions get policy checks. High-risk actions require human oversight

Deploys Over Your Existing Infrastructure

Context OS sits between your systems of record and agent frameworks. No rip-and-replace. No migration. 4-week deployment

Systems of Record

SAP
Oracle
Salesforce
ServiceNow
Workday
Microsoft 365

Data Platforms

Snowflake
Databricks
BigQuery
Redshift
Azure Synapse
Kafka

Security & Observability

Splunk
Datadog
CrowdStrike
Palo Alto
Elastic
PagerDuty

Agent Frameworks

LangChain
CrewAI
AutoGen
Custom MCP
OpenAI Agents
Amazon Bedrock

Frequently Asked Questions

No. Context OS connects to 300+ systems without data migration or workflow disruption, deploying over existing platforms in about four weeks

Traditional AI governance relies on prompts and guardrails, which can fail. Structural enforcement embeds policies and authority into the decision path, preventing non-compliant outputs entirely

Context OS gives all agents a shared, governed context with defined identity, scoped authority, and access rules. Delegated actions remain controlled, and every decision produces an auditable trace

ElixirData meets SOC 2 Type II, ISO 27001, GDPR, and HIPAA standards, with FedRAMP in progress. Context OS deploys on-prem, in VPCs, at the edge, or as a managed service with full isolation and data residency controls

Ready to See Context OS in Action?

See how Context OS deploys over your existing infrastructure in 4 weeks — with structural governance from day one