CLEOS — The AI Operating Substrate

The Problem

Ungoverned AI isn’t just risky.
It’s a financial catastrophe.

The enterprise AI boom is generating massive waste — in compute costs, failed projects, hallucination losses, and now energy consumption at a scale that is reshaping global power grids.

$67.4B

Lost to AI hallucinations in 2024

47% of enterprise AI users made at least one major business decision based on hallucinated content. Only 22% of Fortune 500 companies have formal AI validation policies.

AllAboutAI / Deloitte 2024

80%

AI project failure rate

Twice the failure rate of non-AI technology projects. 42% of companies abandoned most AI initiatives in 2025 — up from 17% in 2024. 95% of GenAI pilots failed to deliver measurable P&L impact.

RAND Corporation / MIT / S&P Global 2025

23✗

Token multiplication per agentic session

A 1,000-token query with 5-step agentic chaining balloons to 23,000 total tokens. Without persistent memory, every session re-pays this cost in full. At Claude Sonnet 4 pricing, that compounds to millions monthly at enterprise scale.

360Strategy / Alan Turing Institute 2025

4.3h

Lost per employee per week to AI verification

Employees spend 4.3 hours weekly verifying AI outputs — equivalent to $14,200 per employee per year. For a 500-person AI-using organization: $7.1 million annually in pure fact-checking overhead.

Suprmind AI Research Report 2026

165%

Data center power demand growth by 2030

Global data center electricity demand will more than double by 2030, reaching ~945 TWh — roughly Japan’s entire annual electricity consumption. AI workloads are the primary driver.

Goldman Sachs / IEA 2025

$85K

Average monthly enterprise AI compute spend

Up 36% year-over-year. 45% of organizations will spend over $100K/month in 2025, up from 20% in 2024. Computing costs expected to climb 89% between 2023–2025, with every executive surveyed canceling AI projects due to cost.

CloudZero State of AI Costs 2025 / IBM

The Platform

AI doesn’t get smarter.
It gets a better memory.

Every AI session today starts from zero. CLEOS changes that permanently — at the infrastructure layer. Persistent context, enforced governance, and a self-improving intelligence pipeline that eliminates the cold-start waste that is costing enterprises millions and pushing power grids to capacity.

CLEOS runs as a native MCP server with a four-layer governance architecture that enforces policy, captures every action, and injects precision context — before, during, and after every AI task. The system doesn’t just assist. It governs.

Three memory modes — adapt to any workflow

SIMPLE

Sequential conversation history. Fast, lightweight, zero setup.

THREADED

Topic-organized conversations with semantic grouping and branching.

STRUCTURED

Full project intelligence with structured context management. Enterprise-grade.

Session Intelligence Pipeline

HOOK 1

Session Start — Precision context injected from memory

↓

HOOK 2

Pre-Execution — Policy enforced before every action

↓

HOOK 3

Post-Execution — Full audit trail captured in real time

↓

HOOK 4

Session Stop — State finalized and indexed to memory

↓

PIPELINE

Microservices — Embed → Index → Learn → Refine

↓

OUTPUT

Next Session — 91% less compute. Fundamentally better AI.

See the Difference

What changes when AI has a memory.

Toggle between a world without CLEOS and a world with it.

Before CLEOS

After CLEOS

Capabilities

14 capabilities. One operating substrate.

Everything serious AI deployments require — memory, multi-agent routing, control, intelligence, governance, security, and sustainability — purpose-built and production-ready.

🧠

Persistent Memory Layer

Session-to-session context that actually persists. CLEOS captures, indexes, and injects the right memory at the right moment — eliminating the cold-start problem and the 23✗ token multiplication that comes with it.

Core Architecture

🔒

Four-Layer Governance

Policy enforcement at every stage: Session Start, Pre-Execution, Post-Execution, and Stop. Bad behavior becomes impossible — not just discouraged. Hooks block non-compliant actions before they execute, not after.

Core Architecture

⚡

Intelligence Microservices

A self-refining pipeline: embed, index, learn, and improve with every interaction. The system doesn’t just remember — it compounds intelligence over time, reducing redundant computation with every session.

Core Architecture

🔍

Semantic Context Search

AST-based code and document intelligence surfaces the most relevant files, cases, or records from thousands in under 500ms. Precision retrieval eliminates brute-force context loading — directly reducing compute and energy costs per session.

Efficiency

🌱

Compute Efficiency Engine

91% of AI compute waste eliminated per session through precision context injection, prompt caching, and intelligent session state management. At enterprise scale, this translates directly to megawatts of power demand reduced and hundreds of thousands saved annually.

Efficiency

♻️

Carbon-Aware Workload Management

With AI inference projected to consume 347 TWh globally by 2030, a 91% reduction is not a feature — it’s an environmental imperative. CLEOS is the infrastructure layer that makes responsible AI deployment at scale possible.

Sustainability

📋

Regulatory-Grade Audit Trail

Every tool call, every decision, every file accessed — captured with full provenance. Satisfies OCC, HIPAA, FedRAMP, FDA 2025 draft guidance, EU AI Act, and SOC 2 audit requirements natively. No bolt-on compliance layer needed.

Compliance

🤖

Automated Compliance Reporting

Audit trails aren’t just captured — they’re structured for regulatory consumption. Generate compliance reports, decision provenance chains, and model risk documentation without manual effort. Built for the OCC, NDAA, and EU AI Act mandates taking effect in 2025–2026.

Compliance

🛡️

Zero-Trust AI Access Control

Role-based, least-privilege access enforcement for AI agents and users. Pre-execution hooks validate who can access what data before any action executes — enforcing data boundary compliance for HIPAA, classified data handling, and attorney-client privilege at the infrastructure level.

Security

📡

Real-Time AI Monitoring

Live dashboards of every active AI session — what tools are being called, what data is being accessed, what policy violations were blocked. Full observability across all AI workloads without instrumenting individual models or agents.

Observability

🤝

Multi-User Session Coordination

Real-time awareness across teams with private thread isolation. Multiple AI agents and human collaborators share context without exposing sensitive session contents. Conflict detection, role-gated visibility, and team-shared knowledge — all enforced at the infrastructure level.

Collaboration

🤖

Multi-Agent Orchestration

Route queries intelligently across 6 AI models — Claude Haiku, Sonnet, and Opus; GPT-4o; OpenAI o1; and local Llama — with intelligent routing to the right model for each task. One platform, full model flexibility. Switch providers without losing memory, governance policies, or audit history.

Orchestration

🔗

Model-Agnostic Architecture

CLEOS is the infrastructure layer beneath the model — not locked to any single LLM vendor. Deploy on any cloud, swap models as the market evolves, and maintain full memory continuity. Your infrastructure investment compounds regardless of which model wins.

Portability

🔐

Credential Leak Prevention

Automatically detects and blocks sensitive credentials and secrets before they ever enter AI context or get transmitted. 100% detection rate in production. Zero credential leaks — a non-negotiable for enterprise security teams.

Security

Environmental Impact

AI has an energy problem.
CLEOS is the solution.

Data center power demand is growing 165% by 2030. AI inference is the primary driver. A 91% compute reduction isn’t just a cost story — at hyperscaler scale, it’s a megawatt story.

91%

AI compute waste eliminated per CLEOS session

The IEA projects AI inference will consume 347 TWh globally by 2030. Apply a 91% reduction and you recover approximately 315 TWh annually — equivalent to removing 28 million U.S. homes from the grid for a year.

At average U.S. industrial electricity prices, that represents approximately $22 billion in annual electricity savings at 2030 AI adoption scale. Every enterprise deployment of CLEOS today is a measurable step toward that number.

By the numbers · IEA / Goldman Sachs / Schneider Electric

AI inference energy · 202515 TWh

AI inference energy · 2030347 TWh

Saved with CLEOS · 2030~315 TWh

Equivalent to powering28M homes / yr

Annual $ electricity savings~$22B

10✗

More energy per AI query vs. Google search

Long-context multi-turn AI sessions can use up to 40 watt-hours — vs. 0.3 Wh for a standard search. Context reprocessing without persistent memory multiplies this on every session.

Epoch AI / IEEE Spectrum 2025

$580B

Spent on AI data center infrastructure in 2025

Global AI-focused infrastructure spend. Data centers consuming as much electricity as 100,000 households each — with next-generation campuses projected to consume 20✗ more.

IEA Energy and AI Report 2025

48%

Rise in Google’s greenhouse gas emissions since 2019

Attributed directly to AI data center expansion. Microsoft reported a 29% emissions increase since 2020 for the same reason. AI compute waste is not an abstract problem.

MIT Technology Review 2025

Session TypeCompute UsedEnergy CostWith CLEOS

Standard agentic session (no memory)

23,000 tokens

~$0.34/session

↓ 91% → ~$0.03

Long-context document review (no cache)

200K tokens full reload

~$3.00/session

↓ Precision inject only

Multi-step compliance workflow

Re-runs from scratch

Full cost ✗ sessions

↓ Persistent state reused

Team development session (5 engineers + AI)

5✗ full context loads

5✗ energy cost

↓ Shared session layer

Markets

Where AI governance
isn’t optional — it’s mandated

The industries spending the most on AI are the same ones where ungoverned AI carries the highest cost. CLEOS was built for exactly this inflection point.

🏦

Financial Services

Every AI decision, audited. No exceptions.

23% of enterprise AI spend · Largest buyer segment

🏥

Healthcare & Life Sciences

AI that remembers the patient. Every time.

$928B market by 2035 · Fastest growing sector

⚖️

Legal Services

Privileged. Persistent. Provable.

9.7% tech spend growth · 53% have no AI policy

🏛️

Federal Government & Defense

Mission-ready AI. Accountability built in.

$13.4B active defense AI spend · NDAA mandates

🔬

Pharma & Biotech

Drug discovery memory that compounds over time.

$16.5B AI market by 2034 · FDA requires AI provenance

💻

Enterprise Engineering

Ship faster. Forget nothing. Break nothing.

$4B AI coding spend · Up 7× year over year

Financial Services

Healthcare

Legal

Gov & Defense

Pharma & Biotech

Engineering

Financial Services

Every AI decision,
audited. No exceptions.

Financial services is the single largest enterprise AI buyer — and the sector where AI errors are most catastrophically expensive. 95% of institutions have experienced an AI incident with financial loss. Regulators including the OCC, SEC, CFPB, and EU AI Act are converging on mandatory audit trails and explainability by 2026. CLEOS is the infrastructure that makes compliance-grade AI possible out of the box.

Agentic compliance monitoring — Persistent context eliminates re-analysis of stable rules, cutting compliance ops costs by 20–60%.

Credit risk governance — Four-layer hooks enforce access controls and decision boundaries per OCC model risk management requirements.

Fraud detection provenance — Every AI inference is captured with full traceability, satisfying FCRA and ECOA explainability requirements.

23%

of all enterprise AI spend — largest single sector by budget

95%

of institutions have experienced an AI incident with financial loss

of global revenue — maximum EU AI Act fine for non-compliance

Who buys

Chief Risk Officer

Chief Compliance Officer

Chief Data Officer

Head of Model Risk

Healthcare & Life Sciences

AI that remembers
the patient. Every time.

Healthcare AI is the fastest-growing enterprise sector at 37.7% CAGR. 77% of major health systems cite immature AI tools as the top adoption barrier. HIPAA requires audit trails for any AI touching patient data. New state laws impose per-violation penalties up to $200,000 for non-compliant AI deployments. CLEOS provides the governance layer that makes clinical AI safe, auditable, and cost-effective.

Ambient clinical workflows — Persistent memory eliminates clinician re-briefing across patient encounters.

Prior authorization AI agents — Multi-day workflows handled with persistent state and HIPAA-compliant data isolation.

Clinical trial governance — FDA 2025 draft guidance requires AI audit provenance for IND, NDA, and BLA submissions. CLEOS is native.

$928B

projected healthcare AI market by 2035 at 37.7% CAGR

77%

of health systems cite ungoverned AI as the top adoption barrier

$200K

per-violation penalty ceiling under new state AI healthcare laws

Who buys

CMIO

CIO

VP Revenue Cycle

Chief Compliance Officer

Legal Services

Privileged.
Persistent. Provable.

Legal tech spending surged 9.7% in 2025 — yet 53% of firms have no AI policy. Over 600 AI hallucination cases are on record, with courts disqualifying firms for AI-fabricated citations. At partner billing rates of $900–$1,500/hour, context loss between sessions is a quantifiable billable liability. CLEOS closes the governance gap entirely while preserving attorney-client privilege at the infrastructure level.

Matter intelligence persistence — Full matter context retained across complex litigation. Policy hooks enforce document boundary isolation for privilege.

Contract review governance — Every suggestion and acceptance captured, creating a defensible review record for M&A due diligence.

Regulatory monitoring — Corporate legal teams eliminate redundant AI re-analysis across changing regulatory landscapes.

$10.8B

legal AI software market projected by 2030

600+

documented AI hallucination cases with bar sanctions and malpractice exposure

9.7%

legal tech spend growth in 2025 — fastest ever recorded

Who buys

Director of Legal Technology

General Counsel

Legal Operations

Firm CIO

Federal Government & Defense

Mission-ready AI.
Accountability built in.

FY2025 and FY2026 NDAA both explicitly mandate audit trails, explainability, and model governance for DoD AI. $13.4B in defense AI spending flows to contractors who demonstrate governance readiness. OMB M-25-22 requires AI governance terms in all contracts effective September 2025. CLEOS is architecturally aligned with every requirement out of the box.

Intelligence analysis governance — Persistent memory with policy hooks that enforce data boundary compliance across classification levels.

Acquisition compliance AI — Full audit trail of every AI-assisted contracting decision satisfies FAR accountability requirements.

Multi-agent mission coordination — Session awareness enables coordination without exposing classified thread contents across clearance levels.

$13.4B

active defense AI spending flowing to governance-ready contractors

100%

of new DoD AI contracts require audit trail capability under FY2026 NDAA

Sep ’25

OMB M-25-22 effective — AI governance required in all new contracts

Who buys

Program Executive Officers

AI Mission Owners

Prime Contractors

DIU

Pharma & Biotech

Drug discovery memory
that compounds over time.

The cold-start problem in drug discovery isn’t inconvenient — it’s a $1.4B problem (average cost to bring a drug to market). Every session re-analyzes the same failed compounds, same targets, same assay data. CLEOS eliminates that waste. FDA’s 2025 draft guidance on AI in regulatory submissions explicitly requires audit trails and provenance for any AI-generated content in IND, NDA, or BLA filings.

Drug discovery session continuity — AI retains full campaign context across months — hypothesis history, failed experiments, literature anchors.

Regulatory submission provenance — Every AI-generated statement traceable to source data and reasoning chain per FDA 2025 draft guidance.

Multi-site clinical coordination — Persistent state and multi-user coordination across AI agents supporting enrollment and adverse event analysis.

$16.5B

pharma AI market projected by 2034 at 27% CAGR

$1.4B

average cost to bring a drug to market — context waste is measurable

$15B+

AI drug discovery partnership deal value in 2025 alone

Who buys

VP Computational Biology

Head of AI Research

Head of Regulatory Affairs

CDO

Enterprise Engineering

Ship faster. Forget nothing.
Break nothing.

AI coding is the largest enterprise AI spending category at $4B in 2025 — up 7✗ in one year. But 48% of AI-generated code contains security vulnerabilities, and every new session re-ingests full codebase context from scratch. CLEOS solves both. It was built on itself — the product has proven, self-validating use cases and the team has authentic domain authority.

Persistent codebase AI assistant — Architectural decisions and code reviews retained across sessions. No re-briefing. No context loss.

Policy-enforced code governance — Pre-execution hooks block vulnerable patterns before code is generated. Addresses the 48% security vulnerability rate at the infrastructure level.

Multi-agent dev coordination — Multiple AI agents on the same codebase share context, prevent conflicts, and maintain a full audit trail for SOC 2 and FedRAMP compliance.

$4B

AI coding spend in 2025 — up 7✗ YoY, largest enterprise AI category

48%

of AI-generated code contains potential security vulnerabilities

91%

of engineering orgs have adopted AI coding tools — entire sector is addressable

Who buys

VP Engineering

Head of Platform / DevEx

CISO

CTO

The AI Operating Substrate
Every Enterprise Needs

Ungoverned AI isn’t just risky.
It’s a financial catastrophe.

AI doesn’t get smarter.
It gets a better memory.

What changes when AI has a memory.

14 capabilities. One operating substrate.

AI has an energy problem.
CLEOS is the solution.

Standard AI has no memory.
No governance. No learning.

Where AI governance
isn’t optional — it’s mandated

Start free. Scale to enterprise.

Claude-native. Enterprise-ready.
The timing is now.

The AI Operating SubstrateEvery Enterprise Needs

Ungoverned AI isn’t just risky.It’s a financial catastrophe.

AI doesn’t get smarter.It gets a better memory.

What changes when AI has a memory.

14 capabilities. One operating substrate.

AI has an energy problem.CLEOS is the solution.

Standard AI has no memory.No governance. No learning.

Where AI governanceisn’t optional — it’s mandated

Start free. Scale to enterprise.

Claude-native. Enterprise-ready.The timing is now.

The AI Operating Substrate
Every Enterprise Needs

Ungoverned AI isn’t just risky.
It’s a financial catastrophe.

AI doesn’t get smarter.
It gets a better memory.

AI has an energy problem.
CLEOS is the solution.

Standard AI has no memory.
No governance. No learning.

Where AI governance
isn’t optional — it’s mandated

Claude-native. Enterprise-ready.
The timing is now.