AI that does the work. Built into the tools you already run.

Flintlever finds the one workflow where AI will pay off first, wires it into your inbox, CRM and documents, proves it with your own numbers, and then scales it across the business.

A workflow, running

Here's what that looks like, team by team.

A support inbox, wired end to end. AI reads and sorts each email, pulls the customer's record and drafts the reply. A person approves it before it goes out, and the CRM updates itself.

Working automations, not slide decks Your tools, your accounts People approve what matters
Example · Support inboxRunning
Steps6, two use AI
Human checkEvery reply
Runs inYour tools
Why AI stalls

Most companies try AI everywhere and get nowhere.

We start with one workflow, build it properly, prove it pays, and only then pull the lever.

  • The chat window

    Staff paste text into a chatbot and copy the answer back. It helps a little, but the process around it doesn't change.

  • The pilot

    A promising test never connects to real systems, so it never leaves the test.

  • The strategy deck

    A long roadmap with no one assigned to build the first step.

  • No baseline

    Nobody measured the work before, so nobody can say whether AI made it better.

How it works

Adopt. Adapt. Advance.

A flint strikes the spark. A lever lets a small force move something heavy. Every engagement follows the same three steps, in order.

  1. 01Strike the flint

    Adopt

    Find where the first spark will catch.

    We map how work actually moves through your team and pick the one workflow where AI will pay off first: frequent, repetitive and easy to measure.

    • Workflow audit with the people who do the work
    • A baseline of time, volume and cost, in your numbers
    • A one-page plan for the first build
  2. 02Set the fulcrum

    Adapt

    Build it into how your team works.

    We wire triggers, webhooks, APIs and language models into your inbox, CRM, documents and data, with a person approving anything that matters.

    • A working automation, running in your accounts
    • Human review wherever judgment is needed
    • Tested on real cases before it goes live
  3. 03Pull the lever

    Advance

    Scale what works across the business.

    Once the first workflow beats its baseline, we take the same pattern to the next team and the next process, so output grows without adding headcount.

    • Results measured against the baseline
    • Next workflows chosen by payoff
    • Documentation and training so your team owns it
What we build

Workflows, wired end to end.

These are the kinds of work we automate most often. Each one connects AI to the systems you already use, with a person in the loop where it counts. Flip the lever on a card to see the difference.

Support inbox

email→classify→CRM→draft→review
Before

Someone reads every message, looks up the customer and writes each reply from scratch.

Lead intake

form→enrich→score→CRM→alert
Before

New leads wait in a shared inbox until someone copies them into the CRM.

Documents to data

PDF→extract→check→ERP
Before

Invoices, orders and forms are retyped into another system by hand.

Reporting

sources→merge→summarize→send
Before

Monday morning goes to pulling numbers from four tools into a slide.

Team knowledge

question→search docs→answer→cite
Before

The same questions about policy, pricing and process interrupt the same senior people.

Team hand-offs

order→ops→finance→notify
Before

Work stalls between teams while people chase updates by email.

Quotes and proposals

request→pull prices→draft→approve→send
Before

Reps rebuild every quote from old files and wait days for pricing sign-off.

Payment chasing

due date→check paid→write reminder→send→escalate
Before

Late invoices sit until someone finds time to write awkward reminder emails.

New hire onboarding

offer signed→accounts→plan week→manager→welcome
Before

HR chases IT, IT chases managers, and the new hire waits for logins on day one.

Scheduling and dispatch

request→triage→find slot→confirm→text
Before

Dispatchers juggle calls, spreadsheets and maps to fit each job in.

Stock and reordering

low stock→forecast→suppliers→draft PO→approve
Before

Someone counts shelves, guesses quantities and emails suppliers one by one.

Meeting follow-ups

call ends→transcript→summarize→tasks→CRM
Before

Notes are scattered, action items are forgotten and the CRM is never updated.

Find your lever

Price the work before you automate it.

Pick a task your team repeats every week and enter your own numbers. It's the same baseline every Flintlever audit starts with.

40%
Your estimate. We measure the real figure against your baseline during the build.
Your lever
0hours back per year for answering routine customer emails
0hours back per week
$0of time per year

people × hours × share × 48 working weeks

Builders, not talkers

How we work.

Working software, not slide decks

Every engagement ends with something running in your business. If a workflow isn't worth automating, we'll say so.

Your numbers, not benchmarks

We measure time, volume and errors before we build and again after, so you see the change in your own data.

People stay in charge

AI sorts, drafts and checks. A person approves anything that touches a customer, money or a decision.

You own what we build

It runs in your accounts, with documentation your team can follow. No black box and no lock-in.

Tools we wire together

  • OpenAI
  • Anthropic Claude
  • Google Gemini
  • Microsoft Copilot
  • n8n
  • Make
  • Zapier
  • Google Workspace
  • Microsoft 365
  • Slack
  • HubSpot
  • Salesforce
  • Zendesk
  • Airtable
  • Notion
  • Webhooks and APIs

We choose tools for fit and cost. If you already pay for something that can do the job, we start there. Logos are trademarks of their owners and don't imply a partnership.

Questions

Before you get in touch.

What does a first project look like?

One workflow, start to finish. An audit to choose it and set the baseline, a build in your tools, and a measured go-live. Scope and price are agreed before any build starts.

Do we need a technical team?

No. We do the build. We need a few hours with someone who knows the work well, and one person who will own the workflow once it's live.

Which AI models do you use?

Whichever fits the job and your data rules: models from OpenAI, Anthropic, Google or Microsoft, or models that run inside your own cloud.

What happens to our data?

Workflows run in accounts you control and use business-grade AI services, not consumer chat apps. We document where each piece of data goes and who can see it.

Start with one workflow

Tell us the task that eats your week.

Send a few lines about the work and the tools involved. We'll tell you whether it's a good first workflow and what an audit would cover.

Email What happens next
  1. You send a short note. The task, roughly how often it happens, and the tools it touches.
  2. We have a short call. We ask how the work moves today and where it gets stuck.
  3. You get a one-page plan. The first workflow, the baseline we'll measure, and what it costs.
Email us