Atomic Agents

A platform to build, run, and manage agentic workflows.

We built it because we needed something secure and enterprise-grade that was still simple enough to embed in a small or mid-sized business, anywhere. It is not something you can sign up for: access comes with the engagement, so every business running on it is one we chose to work with.

Start here

So, what does it actually do?

Everything on one canvas.

Triggers, app steps, AI, branches, approvals and the file it produces, laid out so you can read a whole process at a glance.

See a flow

Say it, and it builds itself.

Describe a process in plain language. The builder picks the steps, wires them together and lays them out while you watch. No developer, no scripting.

How it is built

Agents that answer for you.

Give one a purpose, your knowledge, your systems and your flows. Reach it by chat, by email or on a schedule. Always on, and never onboarded.

Meet the agents

250+ systems. 20,000+ actions.

Microsoft 365, QuickBooks, Salesforce, Teams, Stripe, Shopify and the rest. Connect a system once and every one of its actions becomes a step you can use.

Browse the catalogue

Any AI can call your work.

Publish a flow over MCP and Claude, ChatGPT or your own assistant can run it: on your credentials, under your rules, with the same record kept.

How MCP works

You approve what matters.

Set a threshold. Everything under it simply happens; anything over it waits for a person and picks up the second they answer.

See approvals

You can see what it cost.

Every run, its duration, its outcome and its price. Down to the individual step, rolled up by flow and by the person who set it going.

See the numbers

Workflows

One canvas. Everything the work needs.

Not a diagram of a product. The thing itself. Every automation you build is these six parts in some order, on one surface, where the branch and the approval can be seen rather than described. Point at a part to find it on the canvas.

Drawn from its own node and edge data rather than captured from a screen.

Build by chat

Describe it. Watch it build.

Tell the builder what you want in plain language and it picks the steps, wires them together and lays them on the canvas while you watch. Then you refine it, or we do.

It knows which of your systems are already connected
It places and connects the steps as it goes
It says what it added, and why, at every step

“Every Monday, pull our overdue invoices from QuickBooks, draft a friendly reminder with AI, and email each customer.”

Building your workflow…

Added Schedule · Mondays
Added QuickBooks · Pull A/R aging
Added Filter · overdue › $500
Added AI Agent · Draft collection email
Added Outlook · Send to each customer
Workflow ready: opening the canvas

Managed agents

And an agent that can run it.

Give an agent a purpose, a way of speaking, your knowledge and your systems. Its tools are your integrations and your own flows, so one instruction can set off the entire machine above rather than a single API call.

Finance Ops Copilot

Purpose

Handle day-to-day accounts-receivable and bookkeeping questions for the finance team.

IdentitySenior AR Specialist · warm, concise, professional

Model

Claude Opus 4.8

Knowledge / SkillsPayment Terms 2026.xlsxCollections Playbook

Tools

QuickBooks

Outlook

ExcelSend Collection Emails

Voice

ElevenLabs

ChannelsChat

Outlook

TeamsCall

Which customers are over 60 days past due?

QuickBooks · A/R Aging3 accounts, $42,180 total. Northwind ($21k), Acme ($14k), and Globex ($7k). Want me to draft escalation emails and flag finance?

Yes, send them.

Send Collection EmailsDone: 3 escalation emails sent via Outlook and the finance channel was notified.

Your agents can run your workflows. Turn any flow into a tool an agent can call, so one instruction sets off an entire multi-step automation rather than a single API call. Most agent builders only chain tools; this lets an agent operate the whole machine.

A configuration, not a conversation. What the agent is, before anybody talks to it.

Integrations

Over 250 integrations, and new ones every week.

The platform connects to the systems you already run rather than replacing them. Not a handful of popular ones: more than 20,000 individual actions across the catalogue, so a flow can do the specific thing your process needs rather than the nearest thing available. The number under each name is how many actions that service exposes.

250+: Services connected
20,000+: Individual actions
Weekly: New integrations added

Microsoft 365341 actions
QuickBooks174 actions
Outlook120 actions
Slack139 actions
Notion17 actions
Teams78 actions
Salesforce52 actions
HubSpot81 actions
Stripe87 actions
Shopify68 actions
Google Drive34 actions
Supabase18 actions

A selection of the catalogue. The model providers are in it on the same terms as everything else here, which is what model independence looks like in practice rather than as a claim.

Model Context Protocol

Your flows, as tools for any AI.

Publish any flow over MCP and an assistant calls it the way it calls any other tool: one instruction, the whole automation. It runs on your credentials, inside your workspace, and leaves the same record as any other run.

connect.ca.atomicagents.io

OpenAI
Anthropic
xAI
Google
Meta

One endpoint: Every flow you choose to publish, behind a single address you control.
Your credentials: The assistant never sees them. It asks the platform to act, and the platform acts as you already authorised it to.
The same record: A run started by an assistant is logged exactly like one started by a schedule or a person.

Control

It only acts within the rules you set.

Decide what runs on its own and what waits for a person. Both outcomes are written down, which is the part that matters when somebody asks six months later.

Your rule

When a refund is over $10,000, hold it for Finance.

What ran this morningOutcome
Supplier invoice$1,240ran on its own
Expense reimbursement$860ran on its own
Refund request$12,400waiting on Finance
Purchase order$3,900ran on its own

Set the rule once: By amount, by flow, or on a single step. The rule lives with the automation rather than in somebody's head.
Send it to a person: A named approver, a role, or a channel, and an escalation when nobody answers in time.
Nothing is lost waiting: The run holds its state and resumes at the exact step it stopped on. No replay, and no duplicate side effects.
A record you can defend: Who approved, when, on what evidence, and what the run did next. Kept for as long as you need it.

Health and cost

Know what ran. Know what it cost.

Every execution, its duration, its outcome and its price. Not a monthly invoice you reconcile after the fact, but a number against each flow while it is running.

1,284: Runs this month
99.4%: Completed first try
41s: Median duration
$48.20: Spend this month

One execution · 6 steps · 1 awaiting approval

TimeCost
Triggerwebhook0.4s$0.000
Fetch records1,240 rows8.6s$0.001
AI extractper item, in parallel34s$0.031
Write back3 systems12s · 1 retry$0.002
Approvalover your thresholdwaitingn/a
ArtifactPDF and Excel5.9s$0.004
Total1m 32s$0.038

An illustration of the shape the numbers take, not a report from any client's workspace.

Security and residency

A separate workspace for every client.

Isolation is the default rather than something configured per engagement, and where the data lives is a decision you make rather than one you inherit.

Isolation by construction

Every client gets a separate workspace. The separation is structural, not a permission setting somebody has to remember to apply.

Data residency

Canada or the United States, selected at deployment. The same lever that keeps personal information in a Canadian region.

Your cloud, if you need it

Where a business requires it, the platform runs inside the client's own environment rather than ours.