You can't apply AI to a process no one has made explicit

Stop building against a domain you've misunderstood.

Most expensive mistakes don't start in the code. They start in a room where everyone nodded — and quietly meant something different. Klarik takes the explanations you already have — a discovery call, a walkthrough, an SOP — and turns them into a structured model of the domain your whole team can see, challenge, and align on. So you find the disagreement in week one, not at delivery.

Input · Discovery call

"So when a claim comes in, the adjuster checks the policy first, then…" Confident, spoken, and quietly ambiguous.

Input · SOP / training doc

A procedure written in prose — the real process flow buried in paragraphs nobody re-reads.

Input · Recorded walkthrough

An expert explaining how the system works, out loud, end to end.

One shared model
Process flow, as described
The language experts use
Boundaries & ownership
Open questions, surfaced
Where people disagree
The core insight
The structure is already in the explanation. It just never gets drawn — so nobody notices they disagree.

Anyone can explain how their work actually gets done — in a discovery session, a recorded walkthrough, a written procedure. The actors, the sequence, the boundaries, the shared language are all in there, implicit. But while it stays trapped in prose and speech, every listener fills the gaps with their own assumptions. Klarik makes that structure explicit — so the same explanation becomes a model your team can align on, onboard from, and act on with confidence. And crucially, it shows you the gaps and contradictions while they're still cheap to fix.

The hidden cost

What a misunderstood domain actually costs

These are not edge cases. They are the operating reality in any organization that builds, advises, or delivers against a domain it had to learn first.

30–50%
of total project effort is spent on rework. Much of what teams build, they rebuild — because the target was misunderstood, not mis-coded.1
47%
of unsuccessful projects fail to meet goals due to inaccurate requirements management — not technology, not talent.2
$12.5k
lost per employee per year to poor communication — roughly $1.2 trillion a year across US businesses.3
8–12 mo
for a new knowledge worker to reach full productivity — mostly context gaps and repeated clarification, not training.4

Sources: 1. ScopeMaster, software rework (30–50% of effort); 2. PMI, Pulse of the Profession — requirements management; 3. Grammarly & The Harris Poll, State of Business Communication 2023; 4. Click Boarding, time to full productivity (8–12 months).

"A single misread explanation can send an engagement in the wrong direction for months, or push a team to build the wrong thing well. These are not failures of talent. They are failures of structure."

The failure pattern

How a confident "we're aligned" becomes the wrong build

The problem is rarely that people failed to document. It's that the structure inside an explanation never got captured — so nobody could see the point where two people meant different things. Every organization relies on the same fragile chain.

The moment it matters
Discovery call, design session, or walkthrough
The right people explain how it works. Everyone leaves sure they're aligned — on subtly different versions of the truth.
2 weeks later
Notes are incomplete; context reconstructed from memory
The decision exists, but the reasoning doesn't. Different people remember different boundaries.
6 weeks later
A new person re-asks questions answered months ago
Three follow-up meetings, two partial answers, one senior expert interrupted mid-project.
6 months later
A key expert moves on or changes role
The understanding that was never captured is now gone. The next effort starts from scratch.
At delivery
The wrong thing, built well
The answer was inside the original explanation the whole time. It just never became shared, structured, contestable knowledge.
What Klarik produces

Any explanation → one model the whole team can reason about

One source — a client discovery call, a recorded walkthrough, an SOP, an incident review, an onboarding session — becomes a living, shareable model. Grounded in Domain-Driven Design, so it's rigorous enough to design from and clear enough to learn a domain from.

Process flow, as the room described it

The process as actors, work objects, and activities in sequence — exactly the way it was explained. Visual, editable, shareable. No rebuilding the same picture from scratch before every meeting.

The shared language, extracted

The exact terms your client or domain uses, pulled from how experts actually talk. Prevents the translation errors that compound quietly into misaligned deliverables.

Boundaries, context maps & onboarding assets

How the parts of the domain divide up and relate — the boundaries usually trapped in one person's head — plus reusable context a new hire can absorb in hours, not months.

This is not an AI note-taker. Not transcription. Not a wiki.

Note-takers summarize what was said. Klarik models what it means — the structure underneath the words, including the parts the room hasn't agreed on yet.

Why this matters now

First, someone has to make the work explicit

The same illegibility that causes rework is now the thing standing between you and AI. Before a model can help with how your organization works, someone has to actually capture how it works — the workflows, the shared language, the judgment living in people's heads. Most of that has never left the room. Klarik is where it gets written down in a form you can reason about.

01

Make the work legible

Turn the explanations you already have into an explicit model of how things actually run — not the org chart, the real flow.

02

Decide what's worth it

With the process visible, you can see which parts are well-understood enough to change, automate, or hand off — and which aren't yet.

03

Brief and govern with confidence

A shared, structured model is the context any tool — or any new hire — needs to be pointed at the right thing and checked against reality.

Klarik produces the shared understanding that readiness depends on. It's the map of how work gets done — the prerequisite, not the deployment. What you build on top of that map is up to you.

Why this is different

The defensible layer isn't the AI

Practitioner-built, not speculative

Built by practitioners with 25+ years inside complex, regulated organizations. Domain-Driven Design, Team Topologies, sociotechnical systems thinking — not abstract frameworks, but the methods that structure the extraction.

Any source, not just meetings

Transcripts, recorded walkthroughs, SOPs, training docs, incident reviews. If someone explains how a system works, Klarik can model it — for alignment, for onboarding, or to understand an unfamiliar domain fast.

Surfaces dissent, not just consensus

Most tools flatten knowledge into one agreed story. Klarik keeps the open questions and contradictions visible, because the disagreement nobody named is exactly where the costly mistakes live.

Private by design

The explanations you model are your most sensitive context — client engagements, internal process, expert judgment. Klarik runs in your environment, on your model provider and your keys. Your sources reach only infrastructure you control — never Klarik's, never pooled with anyone else's.

Structure, not search

AI is flooding teams with more output than ever. Searching inconsistent summaries doesn't solve the alignment problem — it is the alignment problem. Klarik imposes structure at the source.

Built from the inside out
"Klarik compresses what used to take 5–7 hours of iterative alignment meetings into a single structured session. One explanation. A shared model. The disagreements out in the open — before anyone builds on them."
Built by practitioners with 25+ years leading enterprise architecture and transformation across regulated industries. The disciplines behind it — Domain-Driven Design, Team Topologies, sociotechnical systems thinking — are the methods used to run discovery, structure knowledge transfer, and kill the repeated conversations that quietly cost organizations millions.
Early pilot signals
5–7h
of iterative alignment meetings compressed into one structured session
↳ capacity returned to real work
50%
faster onboarding into complex domains
↳ experts interrupted less
35%
less duplicated effort across teams
↳ fewer rebuilds of the same thing
60%
less manual review chasing down what was meant
↳ mistakes caught earlier
Early access

Run Klarik on one real source from your world

We're working with a small number of pilot partners. Bring a transcript, a recorded walkthrough, or an SOP from a domain you're modeling — for a client or for your own team. No commitment. One source. A structured model, with the open questions surfaced, that you can use in your next meeting.

Your source stays under your control. Klarik runs in your environment, on your keys and your model provider.

How your data flows: your source is processed by a desktop app on your machine and sent only to the model endpoint you configure — your own provider tenant, under your keys and your terms. It never reaches Klarik's servers and is never pooled with other users'. Point it at a model you host yourself, and processing stays fully offline.

Who feels this most: anyone who has to understand an unfamiliar domain before acting on it — consultants and analysts modeling client domains, architects and product teams aligning before a big build, and leaders who need to know how the work really runs before they change it.