Enterprise Workflow Intelligence
Enterprise AI deployments don’t fail because of bad models. They fail because of ungoverned workflows — SOPs that were never modernized, costs that weren’t modeled before production, and governance that lived in policy documents instead of the infrastructure itself. Cromus is the pre-execution intelligence layer built for teams running AI workflows at scale.
Most enterprise AI initiatives share the same blind spots
Before Cromus, enterprise teams face four compounding problems:
Cost surprise — AI workflow costs aren’t visible until the invoice arrives
Governance debt — behavioral constraints live in documents, not in the workflow infrastructure
SOP modernization backlog — legacy processes aren’t AI-ready and nobody knows which ones to prioritize
Security gaps — uploaded documents enter AI pipelines without safety validation
Of these four, cost surprise is changing shape fastest — it is no longer only about magnitude, but about structure. For two decades, enterprise software was metered by the human seat. AI agents perform work without seat-based logins, and vendors have responded with a second meter: consumption-based agentic pricing charged per action. Salesforce meters agent work in Flex Credits and Agentic Work Units. Microsoft layers Copilot credits onto existing seat licenses. ServiceNow charges for governed operational work through Action Fabric. Enterprises increasingly face a hybrid bill — legacy seat costs plus an opaque, consumption-based agent meter — and most discover the second meter only after agents are already embedded in production, when negotiating leverage is gone. Cromus's Total Cost of Workflow Ownership framework counts every meter a workflow runs — inference, application, and governance — so cost structure becomes a pre-execution decision rather than a post-production surprise.
The full pre-execution intelligence stack
On the roadmap: native simulation of vendor agentic meters — Salesforce, Microsoft, and ServiceNow — inside the Cromus Cost Simulator, extending today's 60+ model inference simulation to the full agentic cost stack.
SOP Modernization at Scale
Upload existing SOPs — PDF or DOCX — and Cromus compiles them into structured SKILL.md workflow specs with AI readiness scoring (0–100), step extraction, and token estimates. The AI Compatibility Engine classifies each SOP: AI Ready, Needs Optimization, Legacy SOP, Modernized, or Fully Automated.
See a demo →Cost Governance Before Execution
The Cost Simulator models per-run and monthly costs across 96 active verified generative AI models from 13 text-generation providers — with real, admin-verified pricing. TypeSafe's input-priced decision model is tracked separately; 14 providers are in the registry. Five simulation modes from Eco to Quality. Prompt caching opportunity detection included. No surprise invoices.
How cost modeling works →Croms™ Waste Scoring
Every workflow receives a Croms™ score — Cromus’s proprietary metric quantifying preventable AI workflow waste across cost (35%), latency (25%), failure risk (25%), and structural gaps (15%). Severity bands: Low, Moderate, High, Critical.
What are Croms™? →ETHOS.md Governance Infrastructure
Behavioral governance specs that travel with the workflow — not stored in a policy document. Auditable, versioned, and open-spec. Every SKILL.md paired with an ETHOS.md and MEMORY.md, with GRAPH.md describing the workflow topology.
Try the ETHOS.md validator →Reality Check Loop
Closes the loop between predicted and actual workflow costs. Tracks adoption status, computes confidence bounds from historical run data, and generates executive-ready accuracy reports. Turns Cromus from a static estimator into a continuous learning system.
How it works →Upload Security Scanner
Multi-layer safety scanning on every SOP upload: magic byte validation, DOCX macro detection, PDF JavaScript scanning, and shell injection pattern analysis. Unsafe files are rejected with threat details before text extraction begins.
See it in action →CO2 Impact Estimation
Workflow-level carbon footprint estimates for organizations with ESG reporting requirements.
Built for enterprise environments
All intelligence is deterministic — zero external LLM calls
PostgreSQL-backed with server-side plan enforcement
Team workspaces with shared skill libraries and version history
Agency and White Label tiers for agencies and internal platform teams
JSON-LD structured data and AI crawler optimization on all public pages
Export to LangGraph, CrewAI, AutoGen, n8n, and more
Enterprise plan
Custom pricing
Unlimited seats, dedicated onboarding, priority support, and custom integrations. Everything in Agency plus the scale and compliance controls your organisation needs.
Contact us to discuss your deployment: contact@cromus.ai
Ready to govern your AI workflows before they run?
Cromus.ai · The AI department you don't have to hire