Clarm GTM brain

Clarm Atlas lets enterprise operations teams build governed AI agents to perform recurring back-office work using approved data and systems.

category

Governed enterprise AI agents

market profile

  • text: Large organizations have recurring work across email, spreadsheets, documents and ERP systems, but automation must satisfy IT and compliance controls.
  • text: Enterprise agent builders compete on low-code usability, integrations, governance and deployment options.

personas

  • title: Head of Operations or Supply Chain
    pains:
    • Staff re-key order emails into ERP systems and chase claims across spreadsheets
    • Automation projects wait in an engineering queue while exceptions accumulate
  • title: CIO or enterprise IT leader
    pains:
    • Must enable business-led automation without uncontrolled access to systems or data
    • Needs reusable permissions, deployment options and integration with existing workflows
  • title: Compliance or risk leader at a regulated company
    pains:
    • Needs to trace outputs and actions to approved sources
    • Must demonstrate controls and audit history for automated decisions

icp

  • text: Large, multi-system businesses with repetitive order intake, claims or allocation work are the primary operational fit.
  • text: Banks, asset managers, healthcare and aviation teams with audit obligations and document-heavy workflows are named target segments.
  • text: Departments with a budget of at least $5,000 per month and access to process owners and IT sponsors fit the published Team offer.

message pillars

  • text: Automate complete operational jobs in existing systems.
  • text: Give operators a no-code way to describe and build agents.
  • text: Use sources and controls approved by IT and compliance.
  • text: Leave traceable evidence for oversight.

objections

  • objection: Can business users accidentally grant an agent excessive access?
    response: Clarm says agent grants can only narrow organizationally approved permissions; validate this against your identity and access model.
  • objection: Can AI safely enter orders or handle regulated work?
    response: Start with a bounded pilot, representative exceptions and owner checkpoints; agree accuracy and escalation thresholds before live writes.
  • objection: Must our sensitive data leave our environment?
    response: The company advertises enterprise self-hosting and other deployment options; verify the exact architecture and contract for the chosen plan.

competitors

  • name: Microsoft Copilot Studio
    why: Low-code agent builder integrates with the Microsoft enterprise ecosystem and governance tools.
  • name: Salesforce Agentforce
    why: Enterprise agent builder competes for workflow automation around customer data.
  • name: UiPath
    why: Automation platform competes for operational processes and enterprise agent workflows.

keywords

  • governed AI agent platform
  • enterprise no code AI agents
  • AI order processing ERP
  • automate customer order emails
  • AI agents audit trail
  • regulated AI workflow automation
  • AI claims processing

voice

  • Operational and concrete
  • Governance-conscious
  • Confident and outcome-oriented

signals

  • text: Operations teams are processing substantial order or claim volumes manually across inboxes and ERP systems.
  • text: A regulated enterprise has an AI initiative stalled on permissions, traceability or audit requirements.
  • text: A department wants to automate a recurring workflow but faces an engineering backlog.

stack

  • ERP
  • Microsoft Teams
  • Claude
  • OpenAI
  • AWS Bedrock
  • GCP Vertex AI

pricing

model: flat
starting price: $5,000 per month for one Team workspace with unlimited agents

motion

sales_led

channels

  • Website
  • SEO
  • LinkedIn
  • YC
  • Customer stories

confidence

high

Founders

  • name: Marcus Storm-Mollard
    title: Founder/CEO
    role: CEO
    bio: I speak 8 languages. Built Clarm to fix productivity (2025-?). Built the world's most accurate consumer goods forecasts using AI at NielsenIQ (2022-24). $0-7m ARR in 2y. Visiting Research Fellow at the University of Oxford; published AI swarm research with a MIT journal (2021). Led AI at Deutsche Bank SeS before AI was cool (2019-21). $10m ARR in 2y. Banker at Deutsche Bank. Financed bridges, markets, hospitals etc from Peru to Taiwan. MSci Physics, Imperial College London.

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