Atomicwork
AI native ITSM and ESM platform that lets enterprises deploy and govern AI coworkers across IT, HR, finance, and legal, each with a role, budget, scoped access, and audit trail, with bring your own models and testing before production.
Atomicwork, based in Palo Alto with teams in Singapore and India, is an AI native platform for IT and enterprise service management that ships with an AI workforce to run it. Founded in 2022 and led by co-founder and chief executive Vijay Rayapati, it is backed by Khosla Ventures, Battery Ventures, and Peak XV, and reached general availability of its AI Workforce Platform in June 2026. Rather than adding a chatbot on top of a ticketing tool, it lets enterprises deploy and govern AI coworkers alongside human teams across IT, HR, finance, legal, and workplace, with the same rigor a company already applies to people, systems, and access.
Its universal AI coworker, Atom, handles frontline requests across Microsoft Teams, Slack, email, portal, browser, and voice, and decomposes into specialist coworkers for hardware, software, security, and other domains that coordinate to resolve complex issues end to end. Every coworker has a defined role, managed credentials, bounded access, a compute budget, and a full audit trail, governed across identity, access, skills, budget, performance, lifecycle, and change management from day one. Atom is grounded in enterprise knowledge through connections to SharePoint, Confluence, and Jira and connects to more than five hundred enterprise tools over the Model Context Protocol, so coworkers take action across systems rather than only surfacing information. Teams can bring their own model harness and choose models from providers like OpenAI, Anthropic, and Gemini, test every coworker's procedures and tools before production, and run their workforce from the United States, Europe, or Asia Pacific to meet data residency needs.
The platform is built around enterprise security and compliance, with SOC 2 Type 1 and Type 2, GDPR, HIPAA, no use of customer data for model training, and a self hosted vector database in the customer tenant, and it can layer on top of existing ServiceNow or Jira Service Management without ripping anything out. It acts across systems through integrations and the Model Context Protocol rather than driving arbitrary computer interfaces. For an IT or service team that wants a governed workforce of AI coworkers with real controls, model choice, and audit trails, especially in the two hundred to ten thousand person range, Atomicwork is a strong and unusually complete fit; a team wanting a lightweight single bot, or pure browser automation, will find it more platform than that.
Vendor details
Canonical URL
https://www.atomicwork.com
Category
Enterprise operations agent
Subcategory
Governed AI workforce for IT and enterprise service management
Funding status
Independent, headquartered in Palo Alto with teams in Singapore and India, founded in 2022 and led by co-founder and chief executive Vijay Rayapati. Atomicwork is backed by leading investors including Khosla Ventures, Battery Ventures, and Peak XV, and grew to more than fifty employees ahead of the June 2026 general availability of its AI Workforce Platform. Customers such as Zuora report roughly fifty percent fewer tickets after adopting the platform, and it is available in the Microsoft Marketplace.
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
Atomicwork connects to more than five hundred enterprise tools over the Model Context Protocol and integrates with Okta, Slack, Workday, GitHub, Salesforce, and Microsoft Entra, with coworkers taking action across systems rather than only surfacing information. Atom grounds in enterprise knowledge through SharePoint, Confluence, and Jira, deploys on top of ITSM platforms like ServiceNow or Jira Service Management, and reaches employees across Teams, Slack, email, portal, browser, and voice.
In practice
Your IT team drowns in repetitive tickets for password resets, access requests, and device issues while real projects wait. Atomicwork's AI coworkers resolve those requests end to end inside Slack or Teams, cutting ticket volume sharply.
Most AI deployments stall in production because no one can govern what the agents can see or do. Atomicwork gives every coworker a defined role, scoped access, a budget, and a full audit trail, so IT runs them like a team.
You want AI coworkers but cannot rip out ServiceNow or Jira to get them. Atomicwork layers on top of your existing service management and puts coworkers to work on day one with a clean path to migrate later.
Sources & related URLs
Research sources
Research notes
Added via Crunchbase agentic discovery CSV, enriched full fidelity 2026-07-07. Categorized Enterprise operations on agentic ITSM and ESM. Unusually complete platform: rare Full on model flexibility (bring your own models) and pre production testing. Independent; backed by Khosla, Battery, Peak XV.
Capability coverage
12.5 / 14 capabilities · 89%
| Integrations & Tool CallingConnects to more than five hundred enterprise tools over the Model Context Protocol and integrations like Okta, Workday, and Salesforce, with coworkers taking action across systems, Atomicwork docs 2026-07-07 | Full |
|---|---|
| Workflow OrchestrationThe universal coworker Atom decomposes into specialist coworkers that coordinate to resolve complex issues end to end, with a natural language workflow engine, Atomicwork docs 2026-07-07 | Full |
| Knowledge Grounding & RAGGrounds coworkers in enterprise knowledge through SharePoint, Confluence, and Jira with retrieval and reranking over segmented, context hydrated data, Atomicwork docs 2026-07-07 | Full |
| Human Oversight & GuardrailsGoverns every coworker with defined roles, scoped permissions, approvals, and spend limits, and escalates cleanly to a human with full context when a request exceeds scope, Atomicwork docs 2026-07-07 | Full |
| Security, Identity & GovernanceHolds SOC 2 Type 1 and Type 2, GDPR, and HIPAA, isolates data in the customer tenant, redacts personally identifiable information, and does not train on customer data, Atomicwork docs 2026-07-07 | Full |
| Observability & AuditabilityProvides a full workforce control plane with complete visibility into every coworker, spend and usage monitoring, and a full audit trail for every action taken, Atomicwork docs 2026-07-07 | Full |
| Memory & State PersistenceIts coworker Atom is built with long term memory that improves at handling requests over time, drawing on accumulated context, Atomicwork docs 2026-07-07 | Full |
| Deployment & Data ResidencyOffers data residency across the United States, Europe, and Asia Pacific and a self hosted vector database in the customer tenant, though full on premise deployment of the platform is not documented, Atomicwork docs 2026-07-07 | Partial |
| Prebuilt Agents, Templates & PacksShips ready to deploy AI coworkers on day one across IT, HR, finance, legal, and workplace, plus a global skills catalog, Atomicwork docs 2026-07-07 | Full |
| Triggers & Channel CoverageProactively detects and triages issues before engineers are paged, triggers rollbacks on failures, and reaches employees across Teams, Slack, email, portal, browser, and voice, Atomicwork docs 2026-07-07 | Full |
| Model Flexibility & RoutingLets teams bring their own agent harness and choose models from providers like OpenAI, Anthropic, and Gemini, built on an ensemble multi model architecture, Atomicwork docs 2026-07-07 | Full |
| APIs, SDKs & MCP ExtensibilityBuilt on the Model Context Protocol with more than five hundred tools, a skills catalog, and a natural language workflow builder using the Claude Agent SDK, Atomicwork docs 2026-07-07 | Full |
| Testing, Debugging & OptimizationLets teams test every coworker's operating procedure, skills, and tools before deploying them to production, Atomicwork docs 2026-07-07 | Full |
| Browser & Computer UseActs across systems through integrations and the Model Context Protocol rather than driving a browser or operating a computer interface as its action model, Atomicwork docs 2026-07-07 | Unable to verify |
Pricing
From around twenty five thousand dollars per year for the Professional plan (up to two hundred fifty users), with Business and custom Enterprise tiers
annual subscription by user tier, with usage based and outcome based options
Included quota
Professional (from around twenty five thousand dollars per year, up to two hundred fifty users): AI coworkers, full ITSM and ESM, and enterprise integrations. Business (flexible pricing, up to one thousand users): the same at higher scale. Enterprise (custom): larger deployments. Teams on ServiceNow or Jira Service Management can deploy the AI Workforce on top with no platform fee.
What is public
A Professional plan from around twenty five thousand dollars per year for up to two hundred fifty users, a Business plan for up to one thousand users with flexible pricing, and custom Enterprise contracts, with usage based and outcome based options.
Billing mechanics
Annual subscription priced by user tier, with a public Professional floor, flexible Business pricing, and custom Enterprise contracts, plus usage based and outcome based options. Deploying on top of an existing ITSM carries no platform fee.
Cost watchouts
Cost scales with user count and coworker activity, usage based and outcome based components can move real spend, and larger deployments move into custom Business or Enterprise pricing.
Variable cost rationale
Cost is driven by user count and by usage based and outcome based components tied to how much work coworkers do, so spend grows with adoption across IT, HR, finance, and other departments.
Additional watchouts
Confirm which tier fits your user count, how usage based and outcome based components price, and how coworker activity scales cost as adoption grows across departments.
Overage / add-ons
Pricing is available in usage based and outcome based models, and scaling users and coworker activity moves a customer up tiers or into custom pricing.
Sales call required
Mixed (some tiers require a call)
Free / trial
Demo and pilot on request; no public free tier
Lowest paid plan
Professional from around twenty five thousand dollars per year for up to two hundred fifty users
Commercial notes
Positioned as a governed AI workforce for the mid market and enterprise, differentiated by model choice, pre production testing, and a full control plane, and able to layer on top of existing ServiceNow or Jira Service Management.
Key ambiguities
Business pricing is flexible and Enterprise is custom, and the split between the fixed annual subscription and usage or outcome based components is not fully public.
Cancellation / refund
Annual contracts, with Professional as a fixed annual entry and Business and Enterprise negotiated; existing customers can go live immediately with no migration or reimplementation.
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