AI agents handle the busywork. Your team handles what matters.
ajan.ai builds AI agents that work inside the tools you already run. They read tickets, update records, chase approvals, and escalate to a human the moment judgment is needed.
A 30-minute call. We'll map one workflow end to end.
Illustrative interface. The figures in it are sample data, not measured results.
Built for the systems your operations already run on
- Salesforce
- Zendesk
- NetSuite
- Slack
- Snowflake
- SAP
Connectors we build against. Ask us about anything that isn't listed.
Agents that actually finish the work
Most AI tools summarize and suggest. Ours take the actions, inside your systems, with a record of everything they touched.
Acts across your stack
Agents read and write in your CRM, ticketing, ERP, and data warehouse through authenticated connectors, not by pasting text between tabs.
Knows when to stop
You set the boundaries: spend limits, approval gates, and confidence thresholds. Anything outside them routes to a named human with full context attached.
Auditable by default
Every action an agent takes is logged with its inputs, reasoning, and result. Export the trail for compliance, or replay a run to see exactly what happened.
Deploys in weeks, not quarters
Start with one workflow, measured against how your team runs it today. Expand once it holds up. No platform migration required.
From one workflow to production
We start narrow and prove it works before anything touches your live systems.
- 01
Connect
We link the agent to the systems the workflow already touches, using scoped, read-only credentials to begin. Nothing is written until you say so.
- 02
Configure
We encode the rules your team follows: the edge cases, the escalation paths, the things that are obvious to your staff and invisible in the documentation.
- 03
Deploy
The agent runs alongside your team in shadow mode first, then takes the queue once its output matches theirs. You keep the kill switch.
Where teams start
The best first workflow is high-volume, rule-heavy, and unloved. These usually qualify.
Customer support
Tier-1 resolution and triage
Agents read the ticket, pull the customer's history and order state, resolve what's routine, and hand the rest to a human teammate with the diagnosis already written.
- Refunds and order changes within policy
- Account and billing lookups
- Routing with full context attached
Operations
Back-office processing
The steps between two systems that nobody wants to own: reconciling records, chasing missing fields, moving a case forward when a document finally lands.
- Order and vendor data reconciliation
- Exception queues and follow-ups
- Status updates across systems
Finance
Invoice and approval flows
Agents match invoices to purchase orders, flag what doesn't line up, and route approvals to the right owner, with the discrepancy spelled out.
- Three-way matching
- Approval routing and reminders
- Anomaly flagging for review
The workflows differ. The shape of the problem doesn't.
High volume, rule-heavy, spread across systems that were never meant to talk to each other, and expensive when it goes wrong.
Financial services
Reconciliation, KYC refresh, dispute handling.
Insurance
Claims intake, coverage checks, renewals.
Healthcare
Prior authorization, eligibility, records requests.
Logistics & supply chain
Exception queues, carrier updates, proof of delivery.
Retail & e-commerce
Order changes, refunds, supplier data.
Manufacturing
Vendor onboarding, quality exceptions, maintenance scheduling.
Telecom & utilities
Provisioning, billing disputes, service escalations.
Professional services
Client intake, timesheets, invoice preparation.
Our engineers sit with your team, not behind a ticket queue
Every deployment is led by a forward deployed engineer who learns the workflow first-hand, on your systems, beside the people who run it today.
We start where the work happens
The first days are spent in the queue with your team, watching the exceptions, workarounds and judgment calls that never make it into the documentation.
We build against your systems
Agents are wired into your live stack early, on scoped read-only credentials, so what we build is shaped by real data rather than a sandbox that flatters it.
We stay through rollout
The engineer who built the workflow is still there when it takes real volume, when the first awkward edge case lands, and when your team wants a rule changed.
We leave something you can run
Rules, escalation paths and audit trails live somewhere your team can read and change them. No dependency on us to adjust a threshold.
The commitments, and where your data goes
Both of these are the sort of thing a buyer has to drag out of a vendor on a call. They are cheaper to answer here.
Shadow mode is free
The agent runs alongside your team on your real queue and we compare its output to theirs. You pay when it matches, not before.
One workflow, fixed fee
No platform licence, no seat count, and no annual commitment before anything works.
You keep the kill switch, and the rules
Escalation paths and thresholds live somewhere your team can read and change without us.
Security and data handling
- Where your data goes
- Your records stay in the systems that already hold them. What we keep is the workflow configuration, the rules your team approved, and the log of what the agent did. Anything beyond that is named and agreed in writing before it moves.
- Model training
- Your data is not used to train models, ours or anyone else's. It runs the workflow you asked us to run, and nothing else.
- Access
- We begin on scoped, read-only credentials. Write access is granted per system, by you, after shadow mode.
- Audit
- Every action is logged with its inputs, its reasoning and its result, and the log is exportable.
- Sub-processors
- This site runs on Vercel and sends demo requests through Resend. A deployment adds only what your workflow needs, named and agreed with you before anything connects.
The things you'd otherwise have to ask on the call
What happens when it gets something wrong?
It escalates rather than guesses. Every action is logged with the reasoning behind it, so a wrong call is visible and traceable rather than buried in a queue, and the thresholds that decide when to stop are yours to change.
What access do you need?
Scoped read-only credentials to start. Write access comes per system, granted by you, only after shadow mode has shown the agent matching your team on real work.
How long until it's live?
Four to eight weeks for a first workflow, and most of that is spent in your queue rather than writing code. What we need from you is one person who knows the workflow well enough to argue about its edge cases, and credentials when you are ready to give them.
What does it cost?
A fixed fee per workflow rather than a platform licence or a seat count, so the number does not move when your headcount does. What it comes to depends on how many systems the workflow touches and how much judgment sits inside it. We will give you a real figure on the first call, and shadow mode runs before any of it is due.
What happens to our data?
The short version is above under Security and data handling; the full policy is on the privacy page.
What don't you do yet?
Quite a lot, and we would rather say it here. We do not take work that turns on legal, clinical or credit judgment; the agent prepares those decisions but a person makes them. Several connectors are read-only today, so the agent can read a record and draft the change while someone else commits it. And if a workflow depends on a system with no usable API, we are not the right fit and we will tell you that on the call rather than three weeks in.
Show us a workflow. We'll show you the agent.
Tell us what your team does manually today. On the call we'll map one workflow end to end and be straight with you about whether it's a fit.
- 30 minutes, no slide deck
- A real workflow, mapped on the call
- An honest answer on feasibility