FDE as a service

Your Forward Deployed Engineering team, packed into software.

Coding, sales and support already have AI agents. Meetext brings them to forward deployed engineering: it deploys your product into every customer's tools, clears their security review, keeps it running and ships what they ask for next.

AITell the agent what you need. It does the work, and asks before anything risky.

2 customer environments free. No card required.

Your product

your-product / mcp

tools/list → approved capabilities
Meetext
The work between.
Handled by Meetext.
SlackNorthstar workspace
# customer-intelligence
J
Jamie Just now

Which accounts need our attention?

Your productYour AI

Two accounts could use a check-in.

Orbit · low adoptionForma · open support issue
get_account_healthRead only
↳ Only this customer's data
Handled by MeetextSecurity review answeredfor Northstar's IT team
Picture it in
Your AI, answering with your customer's toolsInteractive example
  • Customer-specific deployments
  • Real capability validation
  • Customer-written acceptance criteria
  • Human approval before changes
  • Personal data masked before any model sees it
  • A budget and a kill switch per customer
  • Incidents diagnosed as they open
  • An AI agent for any dashboard step, that asks first

What it saves

The work an FDE team does,
without the headcount.

A high-complexity rollout, estimated from stated assumptions rather than measured: a $400K loaded engineer, 80 hours to get each customer live by hand, 14 platforms. It already subtracts Meetext's price and AI usage. Change every assumption →

Saved in the first year

$2.9M

12,981 engineering hours back: the work of about 7.2 full-time engineers.

  • Integrations and getting each customer live9,160h by hand · 241h with Meetext
  • Keeping it working: upkeep, support, incidents2,730h by hand · 468h with Meetext
  • Building what customers ask for3,000h by hand · 1,200h with Meetext

The Meetext Agent

Say what you need.
It does the FDE work.

It sits beside every page of the dashboard. Ask it to add a customer and hand you their install link, email a customer, share a security review or check the fleet every morning. It works through the same actions as the buttons, with your permissions, and nothing changes until you confirm it.

Everything it can do
Agent AILooking at Customers

We got a new customer, Globex. Add them and create a share link for this connection.

Illustrative conversation

  • Any step in the dashboard

    Add customers, connect sources, publish, redeploy, share a security review, invite a teammate. The same actions as the buttons, with the same checks.

  • Asks before it acts

    Every change arrives as a card with Confirm and Cancel. After you confirm, it carries on to the next step.

  • Writes the emails

    To a teammate, or to a customer's contact on record, and nobody else. You read every draft before it goes.

  • Checks on a schedule

    “Every morning, tell me who needs attention.” It runs as you, reports, and proposes rather than acts.

  • Your permissions, per person

    Turn a permission off for somebody on the Team page and it is off for the agent working for them too.

  • Never handles secrets

    Credentials never pass through it, and it never sees the tokens in the links it makes for you.

Your customers get their own agent, which sees only them. It writes the first reading of every incident. Every answer shows what it cost.

The work after the sale

Enterprise software
does not stop at “it works.”

You close the customer. Then the real work starts: their security team, their IT admin, their permissions, their outages, their one more thing. Then you close another customer and do it all again.

That is Forward Deployed Engineering.

Meetext does that job, for every customer, as software.

  1. Security

    “We need your security documentation.”

    A security review written for their environment, with where every claim came from.

  2. IT

    “Who approves OAuth and admin consent?”

    The consent flow for their destination, with each scope and why it is needed.

  3. Customer

    “Our teams need different permissions.”

    Per-customer entitlements, and approval before anything changes their data.

  4. Operations

    “Something broke in our environment.”

    Health checks that caught it, an incident with what changed, and the agent's first reading.

  5. Product

    “Can it do this one more thing?”

    A gap grouped across customers, a drafted pull request, closed when their test passes.

FDE as a service

Everything an FDE team builds,
built in.

14 of 20 live today. The rest are marked, not hidden.

01

Integrate

Get the product into their systems.

  • MCP gateway to customer systemsLive
  • Per-customer deployments and versionsLive
  • Slack, Teams, ChatGPT, Claude and moreLive
  • Private network connectorComing
  • Search over customer documentsComing
  • Legacy portal automationComing
02

Secure

Pass their review, keep their trust.

  • Security review per customerLive
  • Human approval before changesLive
  • Personal data maskingLive
  • Budgets and a kill switchLive
  • Enterprise SSO and SCIMComing
03

Operate

Keep it working, and know when it is not.

  • Health checks and incident responseLive
  • Evals on the customer's own casesLive
  • An AI agent that asks before it actsLive
  • Agent emails and scheduled checksLive
  • Customer status page and incident updatesComing
04

Grow

Turn what they ask for into what you ship.

  • Requests grouped across customersLive
  • Changes drafted as pull requestsLive
  • Adoption and expansion signalsLive
  • ROI reports, QBRs and case studiesComing

The engineering loop

It does not stop
after deployment.

The work is not done because code was written. It is done when the customer's agreed case works.

  1. 1

    Observe

    A customer asks for something the product cannot do, and it becomes a routed item with an owner.

  2. 2

    Connect

    The same need, worded differently by different customers, is grouped into one opportunity.

  3. 3

    Draft

    Meetext plans the files, writes the change, validates it, and repairs it if validation fails.

  4. 4

    Dispatch

    Your repository gets a pull request with the customers who asked and the case it must pass.

  5. 5

    Verify

    After release, the customer's own case runs again. It is closed only when it passes.

Agreed case passed. Deployment verified.

Who does what

Most of it is rules.
The AI part asks first.

Rules, not AI

Runs on its own

Deploys, validates, watches health, opens incidents, masks personal data, holds risky changes and stops at budgets. Predictable, and the same every time.

AI

The agent

Does any dashboard step you ask for, emails teammates and customers, runs checks on a schedule, writes a first reading of each incident, and at the level you allow, drafts fixes as pull requests.

Always a person

You decide

You confirm what the agent proposes, choose how much it may do alone, and set what each teammate, and the agent working for them, may do. Your customers choose what waits for their approval.

Security

Built for the review
your customer will run.

The security model

One credential, one customer

Every installation gets its own token, resolved to exactly one environment.

Approval before changes

Deletions always wait for a person in the customer's workspace.

Personal data masked

Before any client or model reads a result, by the customer's own policy.

Evidence, not promises

Each security claim says whether Meetext observed it or your company asserted it.

Your next customer is waiting.

You build the product.
We take it from here.

Connect a source, approve what ships and send your customer an install link. 2 customer environments free. No card required.