Your AI agents have data. They don't have authority to act
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
Why Existing Tools Can't Close It
Existing tools sit above or below the gap. None fill it.
Data governance catalogs what you have. Decision intelligence simulates what could happen. Neither compiles real-time context, enforces boundaries before execution, or produces evidence that governance was followed.
Data Governance
Catalogs and classifies data assets. Tells you what data you have and who owns it.
Decision Intelligence
Simulates outcomes and optimizes decision models. Tells you what would happen if.
Context Plane + Decision Loop
Two planes. One loop. One operating system.
Enterprise AI fails when it knows something — but is allowed to do everything. Reliable AI systems require two distinct capabilities, connected by a decision loop that learns.
Context Plane
Unify entities, rules, and time-aware state so every agent reasons from the same reality.
Outcome: Shared, conflict-free operational reality
Control Plane
Enforce policy and approvals, routing actions through allow, modify, escalate, or block with auditability.
Outcome: Predictable and defensible actions
Decision Loop
Continuous learning — each cycle improves the next decision
Decision traces & precedent search
Evidence-by-construction
Replay & continuous improvement
Provenance, reasoning, policy evaluations
From Intent to Verified Outcomes
From ambiguous intent to auditable outcomes
ElixirData governs the full decision lifecycle — ensuring every action is authorized, constrained, and defensible before execution.
Compile
Resolve identities, infer constraints, determine authority. Ambiguous requests become explicit decision candidates with Context Graphs.
Enforce
Assemble versioned context. Apply policies, risk thresholds, authority checks. Deterministically approve, escalate, modify, or block.
Prove
Provenance and decision lineage. Reasoning, policy evaluations, and authority checks. Every decision becomes instantly auditable.
Primitives
The atomic units of trustworthy AI execution
Context OS reorganizes enterprise AI around four execution primitives. Not features — foundational constructs. Every agent action flows through all four.
State
The single source of truth. A versioned representation of every entity, relationship, and condition. Every change tracked with full lineage.
Context
Not "more retrieval" — decision-grade compilation. The right information, scoped to the right boundaries, at the right time. 60% token cost reduction.
Policy
Dual-gate governance: evaluated before reasoning commits and before actions execute. Exceptions, escalation, approvals, separation of duties.
Feedback
Learning from real agent work — not vibes, not vanity metrics. Powers 10-17% quarterly accuracy improvements through Agentic Context Engineering.
Connected Intelligence Stack
Unified Data, Context, and Agentic Execution Framework
Connect multimodal data, governed context, and automated agentic actions into one secure, real-time intelligence layer
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 and edge cases
Learn operational rules from real execution, enforce consistently, adapt safely 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
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 / CRO — 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
98% faster audit preparation via policy-aligned automation
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.
This layer is inevitable.
We built it first
Context tells AI what's true. Control tells AI what's allowed. Decision traces tell you why it happened. Context OS unifies all three into a deterministic execution layer enterprises can trust
You can build this layer, or you can buy it