The Decision Harness for Enterprise AI agents
ElixrData Context OS is the Decision Harness for Enterprise AI agents — compiling decision-grade context, enforcing policy and authority before execution, and capturing full-lineage Decision Traces for every action. Stanford proved the harness — not the model — drives a 6x performance gap. Context OS is the governed version built for regulated production
TRUSTED BY ENTERPRISE TEAMS BUILDING GOVERNED AI
The Gap
The Decision Gap: Where Enterprise AI Breaks
Enterprise systems are excellent at recording what happened. They almost never capture why an action was allowed — or whether it should have executed at all. That missing reasoning is where enterprise AI fails
Controlled Environments Hide the Risk
Scoped data and informal oversight make every pilot look ready
Use cases stay narrow to show quick wins
Data is cleaned, curated, and consistently predictable always
Oversight remains informal, assumed, and rarely enforced consistently
Outcome: Successful POCs
Real Constraints Break Everything
Permissions, audit trails, and exceptions expose every gap
Permissions are mandatory, enforced, and audited at scale
Exceptions happen constantly and break happy-path assumptions
Audit trails are required for every action taken
Outcome: Incidents and loss of trust
Authority and Reasoning Are Missing
No system enforces authority before execution happens
Allowed actions are undefined across systems and teams
Ownership unclear when decisions cross boundaries
Constraints go unenforced until risk appears after execution
Outcome: This is the Decision Gap
Three Context Layers — The Industry Built Two
Agents need three layers of context to work in production
Production-grade agents require more than data and knowledge—they need decision context. Only when all three layers align can agents act reliably, safely, and in line with business intent.
Data Context
Metadata, lineage, definitions, quality. The foundation for any data-driven organization.
Provided by Atlan · Collibra · Alation
Knowledge Context
Documents, conversations, people, activity. Organizational knowledge made searchable.
Provided by Glean · Enterprise Search
Decision Context
Policy gates, authority verification, decision memory, evidence trails. The governance layer that makes autonomous execution safe.
This is Context OS — by ElixirData
How Context OS Works
Three primitives. One dual-gate architecture. Every agent action governed end-to-end
Retrieval tools stop at context. Observability tools stop at logs. Context OS enforces policy at two deterministic gates — before reasoning and before execution — so no agent action reaches a system of record without passing both
Context Compilation
Assembles the right information, scoped to the right boundaries, at the right time. Resolves identities, infers constraints, and determines authority — so every downstream decision reasons on validated, versioned enterprise truth.
60% token cost reduction
Decision Governance
Gate 1 evaluates policy before the agent reasons — scoping what it sees. Gate 2 evaluates policy before the agent acts — determining whether the action is allowed, modified, escalated, or blocked. Every gate deterministic. Every decision logged.
2 gates · 4 deterministic action states
Decision Memory
Persistent Decision Traces capture context, policies, authority, action, and evidence — full lineage, never summarized. The same traces feed closed-loop improvement and agents get measurably better without retraining the model
10–17% quarterly accuracy gain
Context OS Architecture
The three-layer architecture behind every governed agent action.
One canonical taxonomy. Three stacked layers. A continuous Feedback Band that turns every execution into institutional learning — without retraining the model
Canonical world state and time-bound context projections compiled at the moment of decision. Every agent reasons on the same validated, versioned enterprise truth — resolved identities, inferred constraints, determined authority. No noise. No drift. No stale retrieval.
Explicit constraints evaluated at two deterministic gates — before reasoning and before execution. Policy is structural, not additive: Decision Boundaries run inside the gateway as middleware, not beside it. Every action is allowed, modified, escalated, or blocked before it touches a system of record.
Persistent Decision Traces capture context, policies, authority, action, and outcome for every agent run — immutable, audit-ready by default, and defensible under OCC SR 11-7 and the EU AI Act. The substrate the Feedback Band reads from.
Decision Memory
Every AI decision. Defensible. Traceable. Learned from.
Traditional AI remembers nothing. Decision Memory remembers everything — what was decided, why it was allowed, by whose authority, and what happened next.
Audit-ready exports are automatically mapped to policies, controls, and regulatory obligations. Decision Traces document evidence, applied constraints, approvals, and consistent controls across time.
See how Decision Traces work
Customer Outcomes
Enterprise Teams building with Context OS
See how leading organizations across industries are using Context OS to cut costs, accelerate workflows, and deliver auditable AI at enterprise scale
We reduced audit preparation time by 98% with Decision Traces. Three weeks of manual review became same-day export.
Context OS transformed our emergency dispatch intelligence. Response time predictions improved by 40%, and every AI-driven triage decision now carries a full audit trail — critical for life-safety operations at scale.
Context OS reduced our token costs by 60% and eliminated the context rot problem. Our agents are faster and more accurate every quarter.
Domains of Control
Start where risk is highest
Domains of Control define how AI decisions are constrained, authorized, and evidenced consistently across the enterprise
Built for Leaders
Built for leaders responsible for AI at scale
The ElixirData Context OS connects your enterprise systems, orchestrates context-aware agents, and delivers governed outputs that teams can act on immediately
Deployments
Deploy where your risk and data live
Drive intelligent, data-driven decisions that reduce costs, accelerate outcomes, and deliver sustained measurable ROI
Resources
Helpful Resources & Blogs
Explore insights, use cases, and expert perspectives on governing AI systems, improving decision control, and scaling enterprise AI with confidence
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Enterprise
Enterprise control without slowing execution
A unified operating layer that governs autonomous systems with precision—balancing oversight, security, regional controls, and access discipline while maintaining operational speed and resilience
Agent Registry
Approve agents, scopes, tools, boundaries, and versions. Full lifecycle management with entitlement enforcement.
AgentOps
Monitor execution in real time. Track boundary violations, policy drift, performance degradation. One-click rollback.
Agent Identity & Access
Scope access to exactly what each task requires. Agents act on your behalf without over-permissioning or added risk.
Evaluation and Optimization
Agent actions are visible and auditable. Built-in monitoring and detailed logs provide traceability, accountability, and control.
Privacy, Security & Compliance
Built on a trusted security foundation meeting SOC 2 Type II, ISO/IEC 27001, 27017, 27018, 27701, and CSA STAR standards.
Data Residency & Isolation
Full data sovereignty with tenant isolation. Deploy to your region with strict residency controls and network-level separation.
Admin & Access Control
Enterprise IAM across your workforce of employees and AI coworkers. Role-based controls, SSO, and audit-ready access management.
By the Numbers
What happens when the harness is governed
Four metrics. Three primitives. One governed harness delivering measurable impact from day one.
Based on ElixrData customer deployments, 2025–2026.
The Decision Harness for
Enterprise AI agents
Context tells AI what's true. Governance tells AI what's allowed. Memory tells AI what happened — so the next decision is better than the last.
Generic harnesses plateau. Context OS compounds.