Flowcraft · AI for operations, with a human accountable

Human-supervised AI teams that work alongside yours

Train. Validate. Build. Run.

We train your people, prove ideas on your own data in 2–3 weeks, ship the software, and then run it with AI agent teams. A named person is always accountable for the result, measured against a metric you choose.

Start with any of the four. You own the code we build with you.

No sales pitch. We'll tell you if we're not the right fit

First proof of concept from USD 4,000, in 2–3 weeks, on your data

Capability that compounds 01 · Train 02 · Validate 03 · Build 04 · Run

Start anywhere. Each one stands alone. Hover a stage to see how it connects. Click to explore it.

Scroll: find your role
Teams we work with
  • Logística Internacional
  • Hapag-Lloyd
  • Arauco
  • Eternity Group
  • Cisternas y Cía. Abogados
  • OficinaVirtual.cl
  • Panere
  • Thatch

Train · Validate · Build · Run. Managed agent teams: first pilots. Agents do the work · Humans own the result. PoC in 2–3 weeks. MVP in 4–6 weeks. 88% use AI · about 1 in 3 have started to scale it (McKinsey 2025). A metric agreed before day one. Open-source stack · Your cloud · Your code. A named human in the loop on every agent team. For operations, IT and leadership teams

Who we work with

Start from the problem you own

Most of our work starts with one of four people. Find yours.

You run operations

Your team spends the day chasing exceptions instead of preventing them

Recognise this?

  • Status lives in spreadsheets, email and WhatsApp
  • Long meetings exist only to find out where things stand
  • Peak season breaks the manual process every year

What we do

We prove the fix on your own data in 2–3 weeks. If it works, we build it and put an agent team on the process, measured against the metric you picked.

90 → 30 min Meeting duration
< 24h Carrier response time (defined SLA)
Starts with An AI proof of concept
You lead IT or digital

Your backlog is measured in quarters, and the business won't wait

Recognise this?

  • Business teams build their own shadow tools
  • Past vendors billed hours, delivered late and left without documentation
  • You'd be the one maintaining whatever AI writes

What we do

We add capacity without hiring: an agent team led by a named engineer with merge authority, a full audit trail, on an open-source stack in your cloud. The platform and the code are yours.

Starts with A build, or an agent team pilot
You own or run the company

You know AI matters. You don't have a team to lead it.

Recognise this?

  • Everyone has ChatGPT and nothing changed
  • The last consultants left slides
  • Your busy season leaves no room for a project

What we do

We start with one session for your leadership team, at a fixed price, timed around your season. You leave with two or three ideas worth testing, and working software comes next, not a report.

7 Own agents in production
Starts with AI workshops & training
You lead innovation in a country unit

Headquarters wants results. Global programs move slowly.

Recognise this?

  • Group IT sets the stack
  • Procurement takes months
  • Pilots don't reach production, so there's nothing to show

What we do

We deliver a proof of concept in 2–3 weeks, inside your infrastructure and compatible with group single sign-on, plus a monthly report formatted for headquarters and a case your sister entities can reuse.

4 months Zero to production with the main carriers (vs. 8–12 months industry standard)
Starts with A pilot conversation
Looking for your sector? Logistics and freight Agri-export
The system

Four ways in. Each one stands alone.

Train your people, test an idea, build the software, or have an agent team run it. Start with the one that fits the problem. If you do more than one, each makes the next faster.

How the loop closes

  • Train → Validate Trained teams frame sharper hypotheses and co-build the PoCs that test them.
  • Validate → Build What survives a proof of concept becomes product scope, with the evidence attached.
  • Build → Run Shipped products need capacity to keep improving. Managed agent teams provide it.
  • Run → Train What agents and their human leads learn in production feeds the next cohort.
  • Run ⇢ Validate The Product BA team runs discovery: stakeholder noise to a signed hypothesis in days.
  • Run ⇢ Build The Product Development team ships inside your squad or takes over a live product.
See all services
Tools

We also build our own software.

Tools we run and maintain ourselves, starting with the Dynamic Query Tool: ask questions of your spreadsheets in plain English, no SQL required.

See our tools
New 04 · Run · Managed AI Agent Teams

Agents do the work. Humans own the result.

AI agents handle the volume. On product teams, a named lead on our side checks the work every week and answers for the result. On operations processes, your people approve what matters. Either way, you pay for an agreed outcome, not for hours.

  • A named human in the loop on every team: our lead on product teams, your people on operations processes
  • A metric you agree with us before day one, plus service-level objectives
  • A weekly review of the real work; a monthly report you can take to leadership or headquarters
AI readiness assessment

How ready is your company for AI?

Everyone claims “AI-ready”

60% of companies report little to no value from AI so far (BCG, 2025).

  • Using ChatGPT like a search box
  • Having Copilot licenses nobody measures
  • A tech team doing something with AI

Real AI readiness

  • Know which processes AI should touch first
  • Measure progress objectively across five dimensions
  • Have something running in production, not only pilots
Self-assessment: score it in two minutes
Drag to score your reality
01 Ad-hoc 1

Individuals experimenting. No shared standard.

02 Ad-hoc 1

Individuals experimenting. No shared standard.

03 Ad-hoc 1

Individuals experimenting. No shared standard.

04 Ad-hoc 1

Individuals experimenting. No shared standard.

05 Ad-hoc 1

Individuals experimenting. No shared standard.

Presets
Your index Illustrative
1.0 / 4.0 25% of leadership

Pilots in motion, nothing compounding

Individuals are experimenting. There is no shared standard, so learning stays local.

Strategy People Data Internal Customer
Exploited

Your weakest dimension is Strategy. That is where competitors will move first.

Spread

0.0 points between strongest and weakest: reasonably even.

Customer gap

Internal and customer-facing capability are aligned. That's rare, and defensible.

Start here · 01 Train AI Workshops & Training Your team isn't building by default yet. Capability first: a cohort moves every other dimension. Explore Train Score it with us in a 30-minute call

Self-scoring is directional · The workshop version is evidenced

Without clear metrics you're flying blind. Where you are today determines what you build next. Where you're weakest determines what competitors exploit.

Case evidence

What changed when the operations team started building

Their tech team had already rolled out Copilot and everyone used ChatGPT. Nothing had changed for the people running operations. Here's what happened when they started building their own tools.

“We thought we understood AI because our tech team added Copilot and most people were using ChatGPT. Then I realized my team was being left behind. We had tools, but no idea what to use when, or how to move fast.”

“Now we've leveled the playing field across the company. We're scaling projects in weeks that used to take months. We're retaining talent because they see we're serious about this. This is an ongoing road, and I don't know exactly where it leads. But we've built a team complemented by Flowcraft where the challenge is technology maturity and learning, not knowledge dependency.”

Attribution

Corporate Manager

Logística Internacional

Logistics

The gap that matters now is the one between you and where your competitors will be in 12 months .

Read the full cases
How we work

No lock-in. No dependency. That isn't a slogan: it's the exit criteria.

Most vendors sell continuity. We build so you could leave: open tooling, your infrastructure, documented hand-over. That includes agent teams. The platform and the code they build are yours. What we keep is our method: the system prompts, skills and memory layer that make our agents work.

  • 01

    We build with you

    Your team's hands on the keyboard, ours alongside.

  • 02

    You own what we build with you

    Code, agents, evals and playbooks from programs, proofs of concept and builds stay in your estate.

  • 03

    Humans stay accountable

    Every agent team has a named person in the loop: our lead on product teams, your people on operations processes.

  • 04

    Your platform, our method

    Agent teams are capacity you pay for by the outcome. The platform and code are yours; the prompts, skills and memory behind the agents stay ours.

Objections, answered

What operations, IT and company leaders ask before the first call

The questions we hear in almost every first conversation. If yours isn't here, bring it to the call.

Ask it directly
01 Where should we start: training, a proof of concept, a build or an agent team?

Start from the problem and who owns it. If your team doesn't build with AI yet, start with a workshop. If you have a specific idea and a metric, a proof of concept answers it in 2–3 weeks. If something has already proved itself, build it. If you have a live product or a repeatable process and not enough people, an agent team adds the capacity. The self-assessment above points to a first step too.

02 How do we implement AI in our operations without disrupting the busy season?

Time it around the season. Training and planning happen off-peak. A proof of concept runs alongside daily work, on a copy of your real data, and asks a few hours a week of the people who know the process. Nothing goes live in your operation until your team has seen it work and agreed it's ready.

03 Will AI replace my team?

No. Agents take the repetitive volume: reading, checking, chasing and drafting. Your people make the calls, handle the exceptions and talk to customers. In the teams we work with, the change is fewer hours on follow-up and more on the work only they can do.

04 Do we have to change our ERP or systems?

No. We build on the systems you already run: your ERP or TMS, email, spreadsheets, even WhatsApp. Agents read from and write to those tools, so your team keeps working where it works today.

05 Who is accountable when an AI agent gets it wrong?

It depends on the team. On product BA and development teams, a named lead on our side reviews the real work every week, approves what ships and answers for the result. On operations processes, your people are the human in the loop: nothing reaches a customer, carrier or authority without their approval, and we build and run the agents, review how they perform with you every week and report the agreed metric monthly. Every agent action is logged, so you can see what happened and why.

06 How is an agent team different from our outsourcing vendor?

An outsourcing vendor sells hours. An agent team is contracted on an outcome: a metric we agree before day one, with service-level objectives. A named person is accountable for it, you see the real work in a weekly review and a full audit trail, and the platform and code are yours.

07 Do we own what you build, or do we end up dependent on you?

Training, proofs of concept and builds: everything we make with you is yours, on open-source tooling in your infrastructure. Agent teams: you own the platform and the code. What we keep is our method: the system prompts, skills and memory layer behind the agents. If you stop, the software keeps running.

08 Our group IT has to approve the stack. Can you work inside it?

Yes. We deploy in your own cloud, work with your single sign-on and security standards, and use open-source components your IT team can review. We share the architecture and security documentation up front, before any data moves.

09 Are we too small for this?

Probably not. We work with companies of 50 to 500 people, and with country units of larger groups that have their own budget. In the EU, about 3 in 10 companies with 50–249 staff already used AI in 2025 (Eurostat). Every engagement starts at a fixed price, so you know the cost before you commit.

10 How fast do we see something real, and what does a proof of concept cost?

A first proof of concept starts at USD 4,000, fixed price. It puts working software on your real data within the first week and a go / no-go decision in your hands within three. In the logistics case, the first working proof of concept took two weeks, and the platform was in production with the main carriers by month four.

Get started

Start with the problem in front of you

Thirty minutes to look at the problem, decide where to start, or hear that we're not the right fit. No sales pitch.

Recommended first step 30 minutes · video call

30-minute call

Want to see whether this makes sense for you? We'd cover:

  • The problem you want solved, and the metric that would prove it
  • Where to start, and why
  • What it would cost and how long it takes
  • Whether we're the right partner at all

No sales pitch. An honest conversation about fit, including telling you when we're not the right partner.