The governed operating system for Enterprise AI agents
ElixirData Context OS compiles decision-grade context, enforces policy and authority before execution, maintains institutional decision memory, and produces audit-ready evidence — so agents are bounded, explainable, and trusted in 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
Four capabilities. One governed operating system.
From compiling context to closing the feedback loop — every agent action flows through all four.
Context Compilation
Decision-grade context, not more retrieval. Assembles the right information, scoped to the right boundaries, at the right time. Resolves identities, infers constraints, and determines authority.
✦ 60% token cost reduction
Decision Governance
Dual-gate policy enforcement. Gate 1 before reasoning. Gate 2 before execution. Every action deterministically allowed, modified, escalated, or blocked.
✦ 4 deterministic action states
Decision Memory
Every AI decision is defensible. Persistent Decision Traces capture context, policies, authority, action, and evidence — creating institutional memory that improves over time.
✦ 98% faster audit preparation
Feedback Loops
Agents that improve every quarter. Closed-loop learning from real execution, not vanity metrics. Powers continuous accuracy improvements through Agentic Context Engineering.
✦ 10–17% quarterly accuracy improvement
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.
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
CIO / CAIO — Enterprise AI Control
Govern how AI systems operate across the enterprise — without embedding business logic into model weights or brittle prompts
Define, enforce, and evolve AI behavior through context and policy, not retraining cycles
6x faster strategic decisions with governed AI control
COO - Operational Standardization
Standardize execution across teams while preserving real-world exceptions, edge cases, and the nuanced realities of complex operational environments
Learn operational rules from real execution, enforce consistently, adapt as workflows evolve
40–70% L1/L2 work automated by learning
CDO — Governed Business Context
Ensure data, definitions, and decisions reflect a single operational reality across teams and systems.
All AI systems reason on the same validated, versioned business context with continuous drift detection
Single source with drift correction across all systems
CFO / CISO— Risk, Audit & Ownership
Ensure autonomous systems operate inside financial, security, regulatory, and audit boundaries — with clear ownership
Autonomy gated by policy compliance, evidence quality, recovery guarantees, and escalation thresholds
Separation of duties with runtime approvals and escalation
Every AI decision is defensible
Decision Traces produce complete records, enabling dramatically faster, audit-ready regulatory reviews
Every AI decision is supported by clear evidence, applied constraints, and documented approvals
98% faster audit preparation via policy-aligned automation
Evidence by Construction
Audit-ready exports are automatically mapped to policies, controls, and regulatory obligations across jurisdictions
Decision Traces document evidence, applied constraints, approvals, and consistent controls across time
Audit-ready exports mapped to policies and obligations
Deployments
Deploy where your risk and data live
Drive intelligent, data-driven decisions that reduce costs, accelerate outcomes, and deliver sustained measurable ROI
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.
Measurable impact from day one
The governed operating system for
Enterprise AI agents
Context tells AI what's true. Control tells AI what's allowed. Context OS delivers both.
A context layer informs. Context OS governs.