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
AI Pilots Succeed in Controlled Environments
AI pilots succeed in controlled environments with clean data, predictable workflows, and informal oversight
Scoped use cases
Clean, predictable data
Informal human oversight
Implicit authority
Outcome: Successful POCs
Real Constraints Break Every Assumption
In production, decisions carry risk, exceptions are constant, permissions are mandatory, and audit trails are required
Permissions are mandatory
Exceptions are constant
Audit trails are required
Justification is non-negotiable
Outcome: Incidents and loss of trust
No System Treats Authority and Reasoning as Data
No system enforces authority before execution. The reasoning connecting data to action was never treated as data
Allowed actions are undefined
Ownership is unclear
Constraints are unenforced
Risk is discovered after execution
Outcome: This is the Decision Gap
ElixirData closes the Decision Gap by governing context and enforcing authority before AI actions execute — not after incidents occur.
Explore Context OS →
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.
From Data to Action
From Enterprise Data to Agentic Intelligence
ElixirData connects enterprise data, builds trusted operational and analytical context, and enables AI agents to take intelligent, governed actions across the organization
Unify Data
Connect enterprise data seamlessly to create a unified, intelligent foundation
Integrate data from applications, databases, logs, metrics, documents, and APIs
Support structured, unstructured, multimodal and real-time data
Break silos without replacing existing systems
Outcome: A single, connected enterprise data foundation
Build Context
Transform raw data into structured, governed, and meaningful business context
Live system signals, events, and workflows
Policies, SOPs, approvals, and access rules
Real-time interpretation across logs, metrics, images, and streams
Outcome: A trusted, governed context layer AI can reason over
Agentic Actions
Enable AI agents to make safe, explainable, and data-driven decisions
Provide context to AI agents and applications via MCP gateways
Enable decisions and actions across text, visual, and event-driven signals
Automate actions with guardrails and human oversight
Outcome: Faster decisions, safer automation, measurable impact
How
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
Compiled, versioned representation of enterprise reality with entities, relationships, rules, and exceptions. This knowledge base enables AI systems to reason about your business domain with enterprise-grade depth
Entities, relationships, temporal state
Organizational rules, definitions, exceptions
Historical precedent and decision traces
Provenance across systems and workflows
Outcome: A shared and conflict-free operational reality
Control Plane
Deterministic constraints on execution with schemas, typed actions, and policy gates. This governance layer ensures every AI decision operates within predefined boundaries and enables progressive autonomy
Policy enforcement before execution
Authority, approvals, and escalation paths
Actions: allow / modify / escalate / block
Automatic evidence and audit production
Outcome: Predictable and defensible actions
Decision Loop
A closed governance cycle that explains outcomes, tracks logic paths, strengthens future performance, and continuously refines oversight through structured accountability
Decision traces and precedent search
Replay and continuous improvement
Evidence‑by‑construction
Provenance, reasoning, policy evaluations
Outcome: Decisions improve with every execution
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
Intent → Structured Context Framework
ElixirData converts intent into governed, structured context that AI systems can safely reason on and act upon
Resolves identities, entities, and relationships
Infers required constraints, dependencies, and risk boundaries
Determines ownership, authority, and approval paths
Outcome: Ambiguous requests become explicit decision candidates
Governed Execution → Policy-Validated Action
ElixirData validates decisions before execution - preventing failures instead of explaining them after the fact
Assembles current, versioned context across systems
Applies policies, risk thresholds, and authority checks
Deterministically approves, escalates, modifies, or blocks
Outcome: Autonomy within explicit boundaries
Verified Outcomes → Evidence by Construction
ElixirData produces evidence as decisions execute eliminating post-hoc reconstruction and forensic guesswork
Provenance and decision lineage
Reasoning, policy evaluations, and authority checks
Tool usage, approvals, execution paths, and outcomes
Outcome: Every decision becomes instantly auditable
What
The Context OS Platform
Seven capabilities. Two layers. One governed operating system that separates what AI knows from what AI is allowed to do — and records why every decision happened
Context OS
The governed operating system for agentic execution. Orchestrates context, control, and evidence across every AI system, agent, and workflow in the enterprise
Unify Data
Connect enterprise data from applications, databases, logs, metrics, documents, and APIs into a single operational substrate. No rip-and-replace — your systems of record become the foundation
Business Context
Transform raw data into structured, governed, decision-grade context. Live system signals, policies, SOPs, approvals, and real-time interpretation — the contextual truth AI reasons over
Build Agents
Design, configure, and deploy governed AI agents. Define scope, tool access, authority boundaries, and escalation logic — agents inherit governance by default
Decision Infrastructure
Deterministic enforcement before execution. Policy gates that allow, modify, escalate, or block. Task templates with explicit constraints, success criteria, and rollback conditions
Governed Agentic Actions
Agents detect, decide, create tasks, and act — within governed boundaries. Multi-agent coordination across systems with context-aware, policy-bound execution
Proof
Three proofs that separate demos from production
Self-serve, rep-free evaluation. See governed agentic execution before you commit.
Policy Gate Demo
Same request, different authority → different outcome. Deterministic enforcement, live.
Decision Replay
Run any past decision "as-of" a different policy, time, or context. Full counterfactual analysis.
Audit Pack
One-click evidence bundle: every trace, policy version, context snapshot, and outcome — exportable.
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