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The Context OS for Agentic Intelligence

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The Pricing Problem with AI

Most AI pricing models are designed for experimentation, not production. Context OS aligns pricing with value, governance, and measurable outcomes, not token consumption

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Governed decisions determine pricing, not usage volume

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Reduced risk is reflected in cost alignment

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Faster audit-readiness drives pricing efficiency

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Human oversight elimination lowers operational expense

Governed Decisions

Pricing focuses on how many enterprise decisions were governed under Context OS, reflecting real operational value

Risk Reduction

Costs scale with measurable risk mitigation, ensuring enterprises pay for impact, not arbitrary computation usage

Audit Readiness

Pricing rewards systems that accelerate audit readiness and compliance, aligning cost with accountability and traceability

Oversight Savings

Eliminating safe, human-in-the-loop oversight reduces operational cost while maintaining governance and reliable AI performance

The Real Cost of Ungoverned AI

Context OS pricing reflects the value of mitigating regulatory, operational, and competitive risks, ensuring enterprises pay for governance and measurable impact rather than raw computation

Regulatory Findings

Non-compliant AI can trigger multi-million dollar penalties and formal consent orders, creating financial and reputational risk

Context OS ensures governance and auditability, preventing violations before they escalate

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Avoid costly regulatory penalties and protect enterprise reputation

Incident Investigation

Ungoverned AI incidents require weeks of engineering to reconstruct events and trace errors

Context OS captures decision lineage in real time, reducing investigation time drastically

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Accelerate incident resolution and significantly reduce operational overhead

Failed Audit

Lack of governance leads to failed audits, remediation projects, and delayed initiatives

Context OS maintains compliance-ready systems, ensuring smooth, auditable operations every time

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Ensure audits pass efficiently without costly remediation

Compliance Reconstruction

Manual evidence assembly for compliance is time-consuming and error-prone in ungoverned environments

Context OS automates evidence collection and decision tracking across systems

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Streamline compliance and reduce manual labor efforts

Competitive Delay

Building AI in-house without governance can delay product launches by 18–24 months

Context OS accelerates safe deployment with governed, reusable AI infrastructure

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Accelerate launches and reduce delays by deploying AI safely with full governance

Operational Risk

Ungoverned AI introduces hidden operational risks impacting productivity, cost, and decision quality

Context OS mitigates risks with monitored workflows, transparent decisions, and accountable execution

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Reduce operational risks while maintaining reliable AI performance

Three Predictable Components

Context OS pricing is designed for enterprise transparency. Each component is predictable, auditable, and aligned with governed AI outcomes, ensuring no hidden costs or ambiguity

Platform License
Governed Decision
Environment & Scale
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Platform License

Covers governance infrastructure consistently, regardless of AI usage

Governed Context Graph automated assembly

Complete Decision Lineage capture

Structural policy enforcement engine for all workflows

Explicit authority verification framework

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Always-on governance infrastructure ensures predictable enterprise control

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Governed Decision Volume

Usage pricing applies only to executed governed decisions, fully metered

Context assembly and comprehensive validation

Policy evaluation and rules enforcement

Decision rights verification and approval tracking

Decision Lineage and rollback

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Transparent pricing scales with executed decisions, not system usage

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Environment & Scale

Pricing reflects production, standby, and deployment realities, not usage spikes

Production environment counted fully

DR/standby environments weighted reduced

Deployment model options

SLA and compliance commitments

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Align costs with operational scope and compliance requirements

Maximizing ROI Through Governed AI

Context OS delivers measurable business impact by accelerating decisions, reducing risk, and improving operational efficiency. Enterprises see faster incident resolution, audit readiness, and substantial cost savings

Faster Incident Resolution

Organizations resolve incidents up to 96% faster, saving time and reducing bottlenecks across workflows


Context OS automates decision capture and governance, drastically shortening investigation and remediation cycles

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Recover engineering time while improving operational reliability

Audit Preparation

Audit readiness improves by up to 98%, reducing compliance overhead and accelerating regulatory reporting


Governed ContextGraphs and decision lineage ensure all evidence is traceable and auditable instantly

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Reduce compliance costs and speed audit cycles

Reduced Manual Oversight

Manual oversight is cut by up to 70%, freeing teams for higher-value work and productivity


Context OS monitors decisions autonomously while enforcing policies and maintaining governance standards

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Boost operational efficiency with fewer human interventions

Faster Decision Cycles

Decision cycles accelerate up to six times, enabling rapid business responsiveness and higher throughput


Context OS provides traceable, governed AI recommendations that streamline enterprise decision-making

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Increase business velocity while maintaining governance and trust

Build vs Buy Economics

The true cost of AI isn’t just dollars — it’s time, risk, and ongoing maintenance

Build In-House

Developing AI internally takes 18–24 months, requiring a team of 12–20 senior engineers, with permanent maintenance responsibilities

High regulatory risk persists during construction, and three-year total cost of ownership often exceeds $3–5M plus opportunity costs

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Context OS

Deploy Context OS in 8–12 weeks with only 2–3 oversight engineers, eliminating the burden of full internal development

Governance is embedded from day one, risks are mitigated, and predictable subscription pricing replaces uncertain TCO

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What CFOs Ask About AI

CFOs want to understand AI risk, compliance costs, and ROI. Context OS provides measurable metrics, traceable decisions, and predictable pricing aligned with enterprise governance goals

AI Risk

Measure AI exposure accurately using Trust Benchmarks and governed decision metrics

Audit Cost

Evidence is produced by construction, reducing audit costs and preparation time

Incident Impact

Decision Lineage retrieval mitigates costs from AI-driven incidents or errors

Scale Safely

Progressive Autonomy enables enterprise scaling without increasing governance risk

ROI Timeline

Most deployments achieve positive ROI within 4–6 months of adoption

Max Exposure

Contractual spend caps ensure predictable financial exposure for AI systems

Frequently Asked Questions

No. Pricing is based on governed decision execution, not tokens, prompts, or model calls. Use any models, agents, and tools — Context OS governs decisions, not computation

One complete execution cycle: context assembly → policy evaluation → authority verification → enforcement → Decision Lineage capture. Retries, rollbacks, or blocked decisions are not double-billed

The opposite. As autonomy grows through Progressive Autonomy, human oversight decreases, improving unit economics. Higher trust levels unlock better rates, contractually defined

Yes. Contractual spend caps are available. Volume commitments can be locked in for better rates, ensuring predictable enterprise budgeting

Request Predictable, Transparent, and Governed AI Infrastructure Pricing

Get customized pricing built on transparency, trust, and measurable governance value — aligned with your enterprise goals, not ambiguous consumption metrics