kataA delivery framework by FXBITS

AI software delivery you can commit to.

kata is a five-layer delivery operating model from FXBITS. It carries AI engineering work from business intent to a live, measured product, with an audit trail your compliance team can stand behind.

the triple thirty — our target

+30%
more features
−30%
fewer defects
−30%
less variance

The targets we commit to and measure against your own baseline over the 12-week pilot — not a claim about past clients.

kata · 型 · a form perfected through repetition

the problem

Most teams bolt AI onto the typing step.

Speed was never the constraint; cost of change is. Ungoverned AI just adds drift, rework, and no trail you can put a price on.

Prefer to skim? Skip the ride →

the model

A form every piece of work flows through.

L1

Engagement Context

We start from the business goal, not the prompt. Intent, constraints, and the KPIs you'll be measured on, captured as plain docs anyone can read.

  • Business intent + success metrics
  • Constraints, non-goals, data boundaries
  • Stakeholders aligned before a line of code
shipscontext doc
L2

Spec Engineering

Before code, the what-and-why is pinned as a versioned spec — a contract reviewed and merged like code, so scope can't quietly drift.

  • Acceptance criteria as a written spec
  • Reviewed and merged via PR
  • A change is a new commit, not a surprise
shipsspec + PR
L3

Agentic Execution

Agents build against the spec, tests first, with every step recorded. A human reviews the PR before anything lands.

  • Red → green → refactor, tests lead
  • Every agent action logged
  • Human approval on every PR
shipsprovenance log
L4

Runtime Guardrails

In production, work runs inside guardrails: tool allowlists, personal data blocked before the LLM, full action logs, and feature flags to roll back fast.

  • Tool allowlist + feature flags
  • PII scanned and blocked pre-LLM
  • Every runtime action audited
shipsaudit pack
L5

Outcome Telemetry

One dashboard ties delivery back to the KPIs from L1. A weekly variance review keeps estimate-versus-actual honest.

  • KPIs from L1, measured live
  • Estimate vs actual within ±15%
  • Weekly variance brief
shipsvariance brief

out of the tunnel

Form, proven.

Five layers, one trail. Here is what the model is worth.

the five layers, in full

The whole model, on one screen.

Skip the ride if you want — here is every layer, what it does, and what it ships.

L1 Engagement Context
Engagement Context

We start from the business goal, not the prompt. Intent, constraints, and the KPIs you'll be measured on, captured as plain docs anyone can read.

ships context doc
L2 Spec Engineering
Spec Engineering

Before code, the what-and-why is pinned as a versioned spec — a contract reviewed and merged like code, so scope can't quietly drift.

ships spec + PR
L3 Agentic Execution
Agentic Execution

Agents build against the spec, tests first, with every step recorded. A human reviews the PR before anything lands.

ships provenance log
L4 Runtime Guardrails
Runtime Guardrails

In production, work runs inside guardrails: tool allowlists, personal data blocked before the LLM, full action logs, and feature flags to roll back fast.

ships audit pack
L5 Outcome Telemetry
Outcome Telemetry

One dashboard ties delivery back to the KPIs from L1. A weekly variance review keeps estimate-versus-actual honest.

ships variance brief

the form, in a word each

Grounded
in business intent + KPIs
Aligned
as a contract, before code
Adaptive
M0–M4, per workstream
Defensible
traced, testable, reviewable
Outcome-led
committed on numbers
trust ladderM0 ManualM1 AssistedM2 AugmentedM3 OrchestratedM4 AutonomousM3 is the day-one default

the outcome we target

The Triple Thirty.

The targets we commit to and measure against your own baseline over the 12-week pilot. Not a claim about past clients — a number we put on the contract and prove.

+30%
features
+20–30% per team / quarter
−30%
defects
−20–35% defect escape
−30%
variance
estimate vs actual within ±15%

Non-negotiable baseline: 100% audit-pack coverage, 100% rollback-drill success.

Put these targets on your baseline →

how it differs

Where kata sits next to the alternatives.

A coding assistant speeds up typing. A generic process catches problems late. kata governs the whole workstream so the trail is built in, not bolted on.

Raw AI coding assistantGeneric SDLC + AIkata governed delivery
Audit trailNone by defaultManual, after the factGenerated every release
Scope driftUnboundedCaught in reviewPinned as a versioned spec
PII / data boundaryUp to the prompterPolicy on paperBlocked before the LLM
RollbackAd hocPer release processFeature-flagged, drilled
Tied to KPIsNoSometimesMeasured live vs baseline

restraint

What we don’t build on day one.

No vector store, no embeddings, no policy engine, no multi-agent. We add each only when a real pain shows up.

for teams that can’t get AI wrong

Provable delivery for high-stakes work.

Fintech, health, energy, public sector: provenance, not promises. The audit trail is built in.

Data sovereignty

Claude in your cloud, in-region. Personal data blocked before the LLM.

Tool composability

Reference integrations ship in the kit, ready day one.

Trust

Opt-in M0–M4 ladder. Human review on every PR by default.

Audit overhead

Generated, not authored. Near-zero cost per release.

Talk through your constraints →

built by FXBITS

Not a first attempt. A track record, applied to AI.

kata is the delivery model FXBITS runs, a software partner that has shipped across healthcare, Industry 4.0, and SaaS for years. The proof of who we are lives on fxbits.io.

Clutch Growth Leader 2024

and Top IoT / medical-software developer, Romania

ISO 9001:2015

plus AWS, Azure, Kubernetes, ISTQB, SAFe, PRINCE2 certified

Healthcare · Industry 4.0 · SaaS

delivered across regulated and high-stakes sectors

A software partner who thinks along with you and understands processes. This leads to a high quality of results and saves extra time and costs.
Lars Petermann · CEO, Premiso AG

proof

We don’t just describe this. We ship it.

Watch one real feature travel all five layers: from a one-line request to a locked spec, a guarded build, and a measured outcome.

Walk through a real feature →

the engagement

From here to validated, in 12 weeks.

01 · Diagnostic
wk 0–2

Kit forked, L1 wired, baseline captured. Walk away with the kit either way.

02 · First feature
wk 3–6

One feature through all five layers, behind a flag.

03 · Validation
wk 7–12

3–5 features. The Triple Thirty, measured against baseline.

04 · Expand
wk 13+

Deepen, broaden, or extend. Your call.

Diagnostic and pilot are separate fixed-price contracts.

Start with a 2-week diagnostic.

Paid, fixed-price, walk-away-friendly. You keep the starter kit either way.

  • Kit forked into your repo in week one, yours to keep.
  • Baseline captured before we touch a line of code.
  • No lock-in. The contract is the structure, not our infra.

Send us a note.

One email opens it. We have pre-filled the basics, so just add a line or two and hit send. Goes straight to the delivery team, and we reply within one business day.

Book the diagnostic

Prefer to write yourself? Email office@fxbits.io. No newsletter, no sales sequence.

questions

What is AI-enabled delivery?

A delivery operating model that turns AI work into predictable, auditable outcomes across five layers, from business intent to a live, measured product.

How do you make AI-generated code auditable?

Every agent action is logged, every LLM call is scanned for sensitive data, and every release ships a generated audit pack.

How is this different from a faster coding tool?

Speed isn’t the constraint. This governs the whole workstream (clarification, alignment, guardrails, telemetry), not just code generation.

Do we get locked into FXBITS?

No. The starter kit is forked into your repo and is yours to keep. The contract is the structure, not our infrastructure.

How does kata compare to AI coding assistants like Copilot or Cursor?

AI coding assistants speed up the typing step inside the editor. kata governs the whole workstream around it: business intent, a versioned spec, guarded agentic execution, runtime guardrails, and outcome telemetry. Use an assistant for code; use kata to make AI delivery predictable and auditable. They are complementary, not alternatives.

Who is behind kata?

kata is built by FXBITS, a software delivery partner based in Cluj-Napoca, Romania, recognised by Clutch as a 2024 Growth Leader and a top IoT and medical-software developer. The team's certifications span AWS, Azure, Kubernetes, ISTQB, SAFe, PRINCE2, and ISO 9001:2015. See fxbits.io for the full track record.