Who we serve

Built for leaders who ask "what does the data say?"

Four situations we step into most often. If one sounds like yours, the flywheel already has a place to start.

Brand Identity

A brand with a story — and a standard.

כלדעת

kol · da'at — read right to left

Founder / CEO

The scaling founder

Growth is real but noisy — every function reports different numbers, and gut feel stops scaling before revenue does.

Where it hurts

  • Metrics scattered across tools that disagree
  • Decisions slow down as headcount grows
  • AI feels urgent but there is no clear entry point

With koldaat

  • One governed data foundation, one truth
  • Forecasts and dashboards that settle debates
  • An AI roadmap sequenced by ROI, not hype

Primary engine · SW Development

CTO / Head of Data

The data & tech leader

The team ships product, but data lives in silos and every AI experiment dies before production.

Where it hurts

  • Pipelines are brittle and hand-maintained
  • LLM prototypes never survive real traffic
  • No evaluation story to justify model choices

With koldaat

  • Automated ETL with quality monitoring
  • RAG/agent systems engineered for production
  • Evaluation baselines that de-risk every release

Primary engine · SW Development

Strategy / Operations

The decision owner

Planning cycles run on spreadsheets and last year's assumptions while the market moves weekly.

Where it hurts

  • Forecasts drift far from actuals
  • Risk surfaces too late to act on
  • Consultants deliver slides, not systems

With koldaat

  • ML demand forecasts with tracked accuracy
  • Early-warning indicators on live data
  • Decision models you keep and re-run

Primary engine · Consultancy

CMO / Growth

The growth leader

Spend keeps rising, attribution keeps blurring, and creative decisions still come down to taste.

Where it hurts

  • ROAS reporting arrives late and vague
  • Audiences built on demographics, not behavior
  • Creative production can't keep up with testing

With koldaat

  • ML budget optimization toward measured ROAS
  • Predictive segments from actual behavior
  • Generative creative tested at scale

Primary engine · Advertising

Different doors, same flywheel — every engagement leaves your data stronger than we found it.

The AI era

Models are everywhere. Advantage isn’t.

Why koldaat, now: the honest answer is about what has stopped being scarce — and what hasn’t.

01

Technology has leveled out

Frontier models are a subscription away for everyone — including your competitors. What used to be a moat is now a utility. "Having AI" no longer differentiates anyone.

02

Data is the scarce asset — trustworthy data above all

The models are shared; your data is not. But volume alone is noise: AI built on unreliable data only automates bad decisions faster. The asset that compounds is data you can trust — complete, governed, verified.

03

The contest is now insight

When everyone holds the same tools, the race is won by whoever turns their data into da’at first — knowledge precise enough to act on, before the market moves.

That is exactly the company we built: one flywheel that makes your data trustworthy, turns it into insight, and proves the result in numbers. In the AI era, that is the whole game — and it is all we do.

A name we have to live up to

Carrying a word like da'at sets a standard. These are the commitments the name holds us to on every engagement:

  • Senior practitioners only — every engagement is led by people who have shipped production AI systems
  • Success metrics agreed in writing before work begins — and reported against, before and after
  • Every claim traceable to data: benchmarks, backtests, and evaluations ship with the work
  • Your data, your models, your keys — full ownership transfers at handover
  • Confidentiality by architecture: least-privilege access, and deployment inside your environment on request
Read the full brand story

Bring us your hardest data question.

One short call is enough to tell whether we can help — and we will say so honestly. Either way, you leave with something concrete: a scoped pilot proposal, success metrics drafted, and a clear view of what your data could be doing for you. No commitment, no pressure.

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