Enterprise AI deployment

AI Transformation for Manufacturing

We build AI agents that do the actual knowledge work in your business, shaped by the judgment your organization already has, until you are AI Native.

Book a discovery callSee the work
  1. 01Absent
  2. 02Ground Truth
  3. 03Build Agents
  4. 04AI Native

AI Agentsfor Enterprise

Agents in the work

Two of them, and what they actually moved.

Not a catalog. Two agents doing ordinary finance work end to end, so you can judge whether the same thing would run on your own numbers.

30%

Improvement in AR collection times

01SterlingReceivables

Cash comes in sooner, because the right accounts get chased in the right order every morning rather than whenever someone finds the time.

  • Reads open receivables straight from SAP, NetSuite or Dynamics, against live tables rather than an export
  • Scores every account on payment history, disputes, days beyond terms and balance
  • Drafts the chase in order of recovery odds, with disputed invoices suppressed automatically
  • Tracks every promise to pay against its date, and reopens the account when it passes
How Sterling works →

$25M+

Chargebacks recouped from disputes

02ClarkPayables

You stop paying twice, and you stop paying for what was never agreed. Chargebacks run at nine to ten percent of receivables in most brands, and that is margin.

  • Extracts vendor invoices from any format and posts the payable into the ERP
  • Three-way match against the purchase order and the goods receipt, line by line
  • Duplicate detection before release, not after payment
  • Checks charges against the contract, so anything outside the agreed terms is flagged rather than absorbed
How Clark works →

Your agents are built around your organization.

The way you price, route, approve and escalate is years of accumulated judgment, and it's a real advantage. It belongs to you and it stays with you, we're not asking you to hand over your playbook or fit yourself into someone else's template. We start from how your business already works, encode that logic into agents built for your environment, and leave you with an operation that runs faster with exactly the things that make you good at it still intact.

Every agent stops at an approval gate until it has earned its way out of one. Nothing releases cash, commits spend or touches a customer without a person saying so.

See all six agents →

What it takes

Bring us the workflow that is costing you.

Transformation does not have to start big. It starts with one workflow, the one you already know is expensive, and a straight answer on whether an agent is genuinely the right thing to point at it.

  1. Weeks 1 to 2

    Assess

    We map the workflow and audit the environment it would run in. Fixed scope, fixed fee, and the output is yours whether or not you go further.

  2. Weeks 3 to 5

    Anchor

    The platform is stood up inside your environment: model gateway, retrieval over your systems of record, evaluation, audit and identity. You own it either way.

  3. Under 90 days

    First agent live

    One agent, one workflow, real transactions, and a person releasing every consequential action.

How this is bought

Nothing large is committed up front. Assess is fixed and small on purpose, and you decide whether to continue on what it finds. If the sequencing is wrong and you should fix something else first, we will say so.

Book a discovery callHow the engagement runs

You bought AI. Nothing does the work.

You have tried the obvious fixes. None of them touched the real problem.

  1. You bought the tools.

    Licences for copilots and assistants. A few enthusiasts got faster. Everyone else kept re-keying invoices by hand. The seats renew whether or not anyone signs in.

  2. You hired the engineers.

    Headcount went up. Throughput did not. They are good people maintaining demos, because nothing they built was ever allowed near a system of record.

  3. You paid for frontier models.

    Real spend on tokens for pilots that never left the sandbox. Nobody would let a model touch a live transaction. So it never touched one.

  4. Your best people are stuck on it.

    The engineers you can least afford to lose are debugging prompts and rewriting evaluation scripts. That is precisely the work this was meant to absorb.

  5. Nobody has seen the value.

    No line on the P&L moved. The board asks about AI and the honest answer is still a roadmap. Two years in, that answer is getting expensive.

The problem was never the model, and it was never your team. Nothing was wired to a system of record, and nothing had permission to act.

That is the part we fix, and it is the only part that turns a pilot into a payable outcome.

Book a discovery call

Execution made better, not rebuilt.

We do not re-platform your business. Your ERP stays where it is, your team stays who they are, and your processes keep the judgment that makes them work. What changes is how much of the execution a person has to do by hand.

Embedded, not advising

Our engineers work inside your team, on your tickets, in your standups. You get people who ship, not a deck and a follow-up.

Fluent in your process

The pricing exception nobody documented. The customer who always gets a call first. That accumulated judgment is your advantage, and it stays yours.

Built to be handed over

The platform runs in your environment and the runbooks are yours. Step four exists so your engineers build the next agent without us.

The commitment

If the number does not move, you do not pay.

We agree what we are measuring before anything is built, against a baseline taken during the assessment.

Metric, baseline and threshold are written down in step one, so nobody is arguing about the definition at invoice time.

This is the same shape as a via ferrata. Someone bolts the line into the rock; everyone else crosses on their own feet.

Book a discovery call

Systems of record

SAP first, because that's where the work is.

Our deepest work is against SAP HANA, reading the ledger live, transforming it, and writing back through the same controls your team already uses. Two of our recent deployments started there. Everything else on this list connects too, and the agents don't care which of them holds the data.

SAP HANASAP S/4HANANetSuiteDynamics 365SalesforceHubSpotSnowflakeDatabricksAzureAWSSharePointOneDriveOutlookGmailSlackTeamsPower BICoupaConcurStripeXeroJiraServiceNowEDI

How the engagement runs.

Four stages from absent to native. The line goes in before anyone climbs, and your team ends up able to walk the route without us.

01

Assess

2 weeks

We map workflows, not org charts. You get a ranked list of candidate workflows with a defensible number attached to each, whether or not you go further with us.

02

Anchor the platform

3 weeks

We stand up the platform in your environment, frontier models, open-weight, or both, depending on what your data residency and cost profile demand.

03

First agent live

Under 90 days

One agent, one workflow, in production against real transactions with a human approval gate on every action.

04

Expand, then hand over

Ongoing

Add agents as trust builds. When you want it in-house, we install the POD operating model with runbooks and evaluation harnesses documented.

Read the full engagement model →

Operators, not an agency.

We ran the technology organisation through exactly this kind of transformation, with a P&L attached and a board asking about the number. Everything below came out of operating, not advising.

$2.5B+

Total GMV scaled across the platform and products we built

120+

Real-world FTEs of capacity unlocked, and counting

25 → 1

Days to close the books, with a reconciliation agent on it

30%

Improvement in AR collection times

More on how we work →

Bring us one workflow.

Thirty minutes, no deck. Pick the process that costs you most in people, errors or delay, and we'll pressure-test whether an agent is genuinely the right answer for it.

  • An honest read on whether that workflow is a good agent candidate
  • What the first deployment would involve, and roughly what it costs
  • An honest answer if the sequencing is wrong and you should fix something else first
Book a discovery call