Support inbox
Someone reads every message, looks up the customer and writes each reply from scratch.
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 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.
We start with one workflow, build it properly, prove it pays, and only then pull the lever.
Staff paste text into a chatbot and copy the answer back. It helps a little, but the process around it doesn't change.
A promising test never connects to real systems, so it never leaves the test.
A long roadmap with no one assigned to build the first step.
Nobody measured the work before, so nobody can say whether AI made it better.
A flint strikes the spark. A lever lets a small force move something heavy. Every engagement follows the same three steps, in order.
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.
We wire triggers, webhooks, APIs and language models into your inbox, CRM, documents and data, with a person approving anything that matters.
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.
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.
Someone reads every message, looks up the customer and writes each reply from scratch.
New leads wait in a shared inbox until someone copies them into the CRM.
Invoices, orders and forms are retyped into another system by hand.
Monday morning goes to pulling numbers from four tools into a slide.
The same questions about policy, pricing and process interrupt the same senior people.
Work stalls between teams while people chase updates by email.
Reps rebuild every quote from old files and wait days for pricing sign-off.
Late invoices sit until someone finds time to write awkward reminder emails.
HR chases IT, IT chases managers, and the new hire waits for logins on day one.
Dispatchers juggle calls, spreadsheets and maps to fit each job in.
Someone counts shelves, guesses quantities and emails suppliers one by one.
Notes are scattered, action items are forgotten and the CRM is never updated.
Pick a task your team repeats every week and enter your own numbers. It's the same baseline every Flintlever audit starts with.
Every engagement ends with something running in your business. If a workflow isn't worth automating, we'll say so.
We measure time, volume and errors before we build and again after, so you see the change in your own data.
AI sorts, drafts and checks. A person approves anything that touches a customer, money or a decision.
It runs in your accounts, with documentation your team can follow. No black box and no lock-in.
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.
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.
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.
Whichever fits the job and your data rules: models from OpenAI, Anthropic, Google or Microsoft, or models that run inside your own cloud.
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.
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.