An engineer of ours, inside your team
Forward-deployed engineers make your organization ready for AI that takes action, not just AI that chats. They migrate you off your legacy platform, build and connect the APIs the agent needs, and turn them into capabilities — real things the AI can do for your customers.
The blocker isn't the AI. It's everything around it.
Years of tickets, macros and integrations lock a support team into the desk it already has, and that lock-in is why most AI programs stall before they start. A forward-deployed engineer’s first job is to break it safely — inventory what you have, and say plainly what moves and what gets rebuilt.
Migration, done for you
We have moved organizations out of deeply embedded desk systems — Zendesk, Intercom, Freshdesk, Salesforce Service Cloud, homegrown — with history, routing rules and knowledge intact. You keep operating while the move happens, and cutover is a date on the calendar instead of a leap of faith.
APIs built, connected, turned into capabilities
Where a system has no API, the engineer builds one; where one exists, they wire it to Atender’s. Every connection becomes a capability — a concrete thing the AI can do for a customer: restart a charger, re-issue an invoice, change a booking. That is the difference between an assistant that explains and one that helps.
AI that acts needs real plumbing
An assistant that restarts a charger or re-issues an invoice needs live, governed access to your systems — not a demo key and good intentions. Forward-deployed engineers build those connections inside your walls: APIs, actions, scoped permissions and the approval rules that decide what the AI may do on its own.
From audit to handover.
Every engagement follows the same arc: map the systems and the data, plan and run the migration, connect and test the actions, then hand over an operation that runs without us.
Audit
We map what you actually have: the desk you are on, the integrations hanging off it, the routing logic nobody has touched in years, and the knowledge scattered between docs, macros and people's heads. Everything gets classified as portable or rebuild before a line of work is committed.
Migrate
History, knowledge base, routing rules and SLA policies move across and are verified against the source. You keep operating on the old system right up to cutover, so the switch is a scheduled event rather than a risk.
Connect
Then the plumbing: APIs, capabilities, integrations and MCP, each with scoped access and an approval policy that says what the AI may do on its own. Every capability is tested before it is allowed near a customer.
Hand over
You get runbooks, named owners, and the tests that prove it works — plus the sessions to go with them. The engagement ends when your team can change the agent, add a capability, and ship without calling us.
A forward-deployed engagement leaves a working platform behind it — the integrations wired, the API and MCP surface in use, the agents live, and the rest of your team onboarded onto it.
Integrations
The connectors your stack already expects — the first thing an FDE wires up, and the last thing you have to think about.
MCP & API
Where custom actions live: the whole platform callable, so an engineer can build what no connector covers.
AI Agents
The agents that use those connections — with the guardrails and approval policies an FDE configures around them.
Onboarding & Consulting
The standard route to live. Forward-deployed engineering is what you add when the technical lift is bigger than a setup.
What an embedded engineer actually does.
See Atender in action
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