Ship AI agents at scale. Safely.
Enterprises are integrating roughly 8x more AI agents this year than last. 88% of them are hitting security incidents in the first year. Only about 14% of agents reach production with full security review. Atlas is the substrate that closes that gap: source receipts on every answer, a human approval gate before anything reaches a customer or a CRM, and a full audit trail your compliance team can replay.
Legacy ran the playbook in production. Email-only deflection at go-live. Then web chat. Then voice agents. Then integrations into their CRM and kit-ordering systems from the Clarm connector catalogue. Twelve months in: 8x total cases processed across all channels, on one substrate, with their team in the approval seat the entire way.
Examples
What you could put on Atlas
Three illustrative workflows. The actual list is whatever your team does with documents, customers, or repeated tasks.
Question and answer for your team
Your sales playbook becomes searchable. Your contracts answer questions about themselves. Your team asks Atlas the way they would ask a colleague who has read every file in the company.
KYC and sanctions screening
Atlas runs customer checks against OFAC and EU sanctions lists, records the audit trail, and flags any match for a human to review. Run it as a daily process or trigger it on each new customer.
Drafts your team approves
Sales follow-up emails, weekly reports, contract review summaries. Atlas drafts. An operator approves. Nothing leaves the system without a human in the loop.
In production today
What scaling agents safely actually looks like
Legacy named publicly with their consent. The three enterprise pilots are anonymized while the work is under NDA. Each followed the same shape: their data, their approval seats, their existing systems, Atlas as the layer that makes shipping AI agents to production a normal Tuesday rather than a board-level incident.
Legacy (healthcare, 12 months on Atlas)
Email → web chat → voice agents → integrated agents
Started with email-only support deflection at go-live. Added the web chat widget once the knowledge base proved itself. Added voice agents for inbound calls. Added agents that integrate with their CRM and kit-ordering system from the Clarm connector catalogue. Year-one result: 8x total cases processed across email, chat, voice, and integrated workflows, on one substrate. Their team has been in the approval seat the entire 12 months.
Swiss private bank
Client review packs and voice-to-CRM
Client relationship officers finish a call, dictate a 60-second voice memo, and Atlas drafts the CRM note, suitability check, follow-up email, and internal chase. The officer approves each one. Coexists with their existing portfolio system.
European fresh-produce importer
Weekly allocations and supplier prep
Atlas reads market demand, production estimates, and shipping schedules from across the systems the team already uses, drafts the weekly allocation pack, and routes exceptions to a human validator. Replaces a manual relay that used to take days.
Swiss airline
Cabin crew onboarding answers
New cabin crew ask Atlas questions about training manuals and bulletins. Every answer cites the document and section it came from. The instructor team owns what counts as approved knowledge.
What it does
AI that actually knows your company
Most AI models learn from the public internet. They do not know your products. They do not know your customers. They do not know your policies. When your team asks AI a question about your business, the answer is a guess.
Atlas builds a private knowledge base from your own documents. Your handbook. Your contracts. Your customer notes. Your compliance manuals. When AI works through Atlas, the answer comes from your own information. Every answer tells you which document it came from.
Without Atlas
AI answers from public training data. Plausible-sounding, often wrong on your specifics.
With Atlas
AI answers from your own information. Every answer points to the document it came from.
How teams use it
Two ways your team uses Atlas
The same Atlas powers both live questions and scheduled work. Most teams use both.
Asking questions
Your team asks Atlas a question. Atlas reads your documents and answers, with the source. Like having a colleague who has read every file in your business.
- ✓Works as a chat widget on your website
- ✓Works as an internal tool in Slack or Teams
- ✓Every answer cites the document it came from
- ✓If the answer is not in your data, Atlas says so
Doing tasks with approval
Atlas drafts something. A human reviews it. If approved, Atlas sends, files, or records it. Common tasks include sales follow-ups, compliance checks, and weekly reports.
- ✓Triggered by a schedule, an event, or a person
- ✓Atlas drafts the work; a human reviews before delivery
- ✓Every action is recorded for audit
- ✓Configured per workflow without a code change
Atlas and Clarm
Atlas is what makes Clarm smart
The Clarm inbound conversion engine runs on Atlas. When Clarm answers a question about your pricing, your product, or your compliance posture, the answer comes from your Atlas-indexed knowledge, not from the public internet.
Clarm inbound widget
The chat product that captures visitors and qualifies buyer intent. Runs on Atlas for live questions and answers grounded in your approved product docs, pricing, and FAQs.
Atlas agent workflows
Scheduled or event-triggered workflows like CRM notes, briefing packs, exception reports, and allocation packs. Each drafts an output for human approval before delivery.
Same brain underneath
Both products read from the same Atlas brain. Whatever knowledge you give one product, the other can use too.
How Atlas is structured
Think of Atlas as a brain for your business
A structure, a bit like a database, for everything AI needs to do useful work in your company. You bring the information. Atlas organises it so AI can use it.
Your documents
Atlas reads everything you upload. Your handbook, your contracts, your manuals, your client notes. Each fact stays traceable to the document it came from.
Your people and products
Atlas builds a map of who connects to what in your business. Your customers, your products, your team, and the relationships between them.
Notes Atlas writes for itself
Atlas summarises the documents it reads so it can reason about them later. A running set of internal notes that update when your information changes.
A diary of every action
Every question, every draft, every approval click is timestamped and stored. Your compliance team can replay any moment in the system.
Templates for repeatable work
Drafting follow-up emails. Running compliance checks. Summarising a meeting. The procedures Atlas knows how to do for your team.
Rules about who approves what
Who can ask what questions. Who has to sign off on what drafts. Who sees the audit trail. The governance configured up front.
Why Atlas
What Atlas guarantees by design
These are properties of how Atlas is built. An operator cannot turn them off.
Every answer points to a source
AI through Atlas always tells you where the information came from. Document name, section, version. If your data does not contain the answer, Atlas says so rather than guess.
A human approves before anything goes out
AI drafts. Your team reviews. Nothing gets sent, filed, or written back to a system without an operator clicking approve. The queue is auditable and exportable.
You choose the AI model, and you change it whenever
Atlas works with Claude, GPT, Azure OpenAI, private open-source models, and self-hosted inference. Switching from one to another is a configuration change. You are not married to a vendor.
Your data stays separated from everyone else
Each customer has their own private knowledge base. The database makes it impossible to mix data between organisations. We verify this in every code change.
You can run it inside your own infrastructure
For regulated industries: Atlas runs entirely inside your private cloud or on premises. No data leaves your network. SOC 2 Type II and HIPAA compliant. Sovereign hosting available for EU, UK, and Swiss deployments.
A new workflow is configuration, not engineering
Atlas is built once. Adding a new workflow means writing a configuration file. A new workflow ships in days.
Many teams, one Atlas
Built to deploy across many teams or portfolio companies
One Atlas, many tenants. A new team or a new portfolio company can start using it without anyone rebuilding what sits underneath them.
What stays the same
The brain that holds your documents. The governance and audit trail. The model router. Built once. Carries every new tenant.
What is separate per tenant
Your data, your rules, and your approval seats. Enforced at the database layer. No cross-tenant leakage by design.
Boundaries
What Atlas does not do
- AI does not take action on its own. It drafts and suggests. A human reviews and approves before anything goes out.
- Atlas does not replace your CRM, ERP, or document tools. It works alongside them as the AI layer.
- Atlas is more than a workflow tool like Zapier or n8n. Those connect apps together. Atlas adds AI that knows your business and an approval step before anything ships.
- Atlas is not robotic process automation. UiPath and similar tools record clicks on existing screens. Atlas runs AI on your data.
- If something is not in your approved data, Atlas will say so rather than make something up.
- Atlas never trains AI models on your data. Models look at your information for each answer. They never learn from it.
- You are not locked to one AI vendor. Atlas works with Claude, GPT, Azure, private models, and self-hosted inference. Switching is a configuration change.
Why this is harder than it looks
Why companies stop trying to build this themselves
Most teams underestimate what has to exist before they ship a single AI workflow. The workflow itself is the visible part. Everything underneath is where the time goes.
Building one workflow is the easy part
The hard part is everything underneath. A way to connect AI to your documents. An approval queue your team trusts. An audit trail your compliance team accepts. A way to switch when your AI vendor changes pricing. Each is its own engineering project. Atlas is all of them.
An in-house AI team is a multi-year commitment
Engineers, payroll, research roadmap. Whatever your team builds in year one may not match what your business needs in year two. Atlas is operating expense you can cancel.
Compliance can pay for part of the spend
SOC 2 Type II, governance built in, contractual no-training. The same buying pattern your compliance team already uses for tools like Aladdin or Onfido. The spend becomes a risk-transfer line item rather than just a software cost.
A small internal AI team will not get there on this timeline
Most internal AI teams ship one application in a year. Five workflows means hiring more engineers or pausing the work they are doing now.
Recent thinking
How the substrate-first design holds up under enterprise pressure
The 2026 agent moment in five posts. Read them in order or jump to the one your team is debating this week.
Start with one workflow
A pilot runs four to six weeks. You pick the workflow. We connect your data. Together we measure whether it works before you commit to a subscription. The pilot fee credits 100% against the first six months.
SOC 2 Type II · HIPAA compliant · On-prem deployable · See pricing