Don't promise your AI is safe. Prove it.

Focaloid governs AI through a nine-phase lifecycle, with a documented go/no-go gate between every phase - from the first intake conversation to the day the system is retired. Mapped to the EU AI Act, the NIST AI RMF and ISO/IEC 42001, so the evidence you produce once counts everywhere. You get a signed governance verdict, not a dashboard of numbers.

Nine phases · eight gatesEU AI Act · NIST · ISO 42001ISO 27001 Certified
Signed & auditableevidence, not claims
9
Lifecycle phases, intake to retirement
8
Documented go / no-go gates
3
Frameworks, one body of evidence
1
Signed verdict per AI system
The Stakes

What ungoverned AI actually costs.

An AI model is an engine. Governance is the rest of the car - the brakes, the dashboard, the service log and a named driver. Without them you don't have a vehicle, you have a fast object with no way to stop it. These are the failures that happen, and none of them are hypothetical.

01
The runaway agent
An agent with refund access wrongly issues 500 refunds overnight. The code compiled fine - the unchecked authority was the problem.
Where it's caughtPhase 3 · Design & architecture - least-privilege tool permissions and a human interrupt on irreversible actions, decided on paper before build.
The controlA tool-permission matrix scoping exactly what the agent may do, plus a hard human-approval step on any irreversible action.
The evidenceThe Architecture Decision Record (ADR) and the tool-permission matrix, in the Phase 3 evidence pack.
Open Phase 3 · Design →
02
Prompt injection & leakage
Untrusted input hijacks the model or exfiltrates data - the OWASP LLM Top 10 threats a functional test never sees.
Where it's caughtPhase 5 · Evaluate & test - adversarial and red-team evaluation for exactly the OWASP LLM Top 10 a functional test can't reach.
The controlInput/output guardrails set in design, then proven under attack with tools like garak and PyRIT before the release gate.
The evidenceThe red-team report and adversarial eval results, attached to the Phase 5 evidence pack the release gate relies on.
Open Phase 5 · Evaluate →
03
Silent quality drift
A system accurate at launch quietly degrades in production. Without monitoring, no one notices until a customer does.
Where it's caughtPhase 8 · Monitor & observe - continuous, sampled online evals plus drift and abuse monitoring, with a human-feedback loop.
The controlLive evals against the launch bar, drift alerts, and traces on every interaction - because traces, not code, are the record.
The evidenceMonitoring dashboards, drift reports and the next-review dates carried in the Living Register.
Open Phase 8 · Monitor →
04
Unaccounted data
PII indexed into a RAG corpus with no lawful basis and no provenance - ungoverned data makes everything downstream ungovernable.
Where it's caughtPhase 2 · Data & knowledge - every dataset and RAG source accounted for, with provenance, PII handling and lawful basis established.
The controlA data inventory with recorded provenance, PII detection and redaction, and a documented lawful basis before anything is indexed.
The evidenceThe data-lineage record and, where personal data is involved, the DPIA - both in the Phase 2 evidence pack.
Open Phase 2 · Data →
The Focaloid Framework

Nine phases across Map, Measure, Manage & Govern.

Governance is a thread, not a final gate. It starts before anyone writes code and doesn't stop until the system is decommissioned. Govern runs across all nine phases; Map, Measure and Manage own their stretch of the build. And it's a loop - Phase 9 feeds its findings straight back into Phase 1.

Map · context & riskMeasure · prove itManage · ship, watch, respondGovern · across every phase
MAP MEASURE MANAGE 1 2 3 4 5 6 7 8 9
Hover a phase for its name · click to open it below · it's a loop - Phase 9 feeds back into Phase 1.
Map · context & risk
Measure · prove it
Manage · ship, watch, respond
Map · Phase 1Initiate & scopeGate · build, or not?
Map · Phase 2Data & knowledgeGate · data cleared
Map · Phase 3Design & architectureGate · design review
Measure · Phase 4BuildGate · post-build readiness
Measure · Phase 5Evaluate & testGate · meets the bar
Manage · Phase 6Review & sign-offGate · go-live
Manage · Phase 7Deploy & releaseGate · release verification
Manage · Phase 8Monitor & observeGate · monitoring review
Manage · Phase 9Operate, respond & retireLoops → Phase 1
GOVERNAI inventory · RACI ownership · go/no-go gates · evidence packs - across every phase.
It's a loop - Phase 9 feeds its findings back into Phase 1.
Eight gates - a documented go / no-go between every phase.Gates are cheap. Drift is expensive. A gate is a five-minute documented decision - not a committee.
Map · Phase 1 Phase 1 · Initiate & scope Gate · build, or not?
Before a line of code, the use case is registered, risk-tiered and matched to its obligations, with success and acceptable failure defined. Most AI risk is decided here, cheaply, by saying "not like that" early.
All nine phases at a glance
One Method · Three Frameworks

Evidence produced once counts everywhere.

The lifecycle is mapped to each framework, so a single body of evidence satisfies all three. No parallel compliance projects, no second team producing the same artifacts in a different format for a different auditor.

Select a framework to see the artifact, phase & clause we produce against it.
The Focaloid governance lifecycle mapped to the EU AI Act, the NIST AI RMF and ISO/IEC 42001, by function.
Function EU AI Act NIST AI RMF ISO/IEC 42001 Phases
Map Risk classification · data governance (Art 10) · DPIA / fundamental-rights assessment
ArtifactRisk classification memo + DPIA
PhasePhases 1–2
ClauseArt 9, 10, 27
Map - context, categorisation, risk identification
ArtifactContext & risk-identification record
PhasePhases 1–3
ClauseMAP 1–5
Cl. 4–6 - context, AI risk & impact assessment
ArtifactContext & AI risk/impact assessment
PhasePhases 1–3
ClauseCl. 4–6
Phases 1–3
Measure Accuracy, robustness & cybersecurity (Art 15) · technical documentation (Art 11)
ArtifactTechnical documentation + robustness/eval report
PhasePhases 4–5
ClauseArt 11, 15
Measure - test, evaluate, benchmark, track
ArtifactEvaluation, benchmark & tracking evidence
PhasePhases 4–5
ClauseMEASURE 1–4
Cl. 8 - operational controls; Annex A controls
ArtifactOperational controls + Annex A control set
PhasePhases 4–5
ClauseCl. 8 · Annex A
Phases 4–5
Manage Conformity assessment · human oversight (Art 14) · post-market monitoring (Art 72)
ArtifactConformity & human-oversight record + post-market plan
PhasePhases 6–9
ClauseArt 14, 72
Manage - respond, monitor, recover
ArtifactResponse, monitoring & recovery record
PhasePhases 6–9
ClauseMANAGE 1–4
Cl. 9–10 - performance evaluation & improvement
ArtifactPerformance evaluation & improvement record
PhasePhases 6–9
ClauseCl. 9–10
Phases 6–9
Govern Quality-management system (Art 17) · accountability, roles & registration
ArtifactAI quality-management system + role register
PhaseAll phases
ClauseArt 17
Govern - culture, policy, accountability
ArtifactPolicy, culture & accountability (RACI)
PhaseAll phases
ClauseGOVERN 1–6
Cl. 5 - leadership & AI policy (the AIMS itself)
ArtifactAI policy & leadership (the AIMS)
PhaseAll phases
ClauseCl. 5
All phases
Which applies to me?
The Composed Stack

No platform closes the seam. Our phase packs do.

The tooling market is split. GRC platforms govern from the policy side. MLOps platforms govern from the model side. They meet - badly - at the Design → Build → Deploy seam, and nobody has closed it. That gap is where ungoverned AI actually ships.

GRC / Compliance-led
OneTrustCredo AIHolistic AISecuritiServiceNowVerifyWise
Strong on policy - stops at the build.
The seam
design → build → deploy
Model-lifecycle / MLOps
watsonx.governanceModelOpMLflowSageMakerVertex AIAzure ML
Strong on models - thin on policy.
Runtime / GatewayLiteLLMDatabricks Unity AI GatewayBifrostNeMo GuardrailsOpenFGA
Observability / EvalsLangfuseArize PhoenixTruLensLangSmithEvidentlyRagasdeepevalThese run the system - but none of them render a verdict.
Focaloid · Nine artifact packs - the connective tissueA per-phase .docx Evidence Pack + .xlsx Living Register, joined by one AI System ID.Where tools report numbers, we render a signed governance verdict - spanning the Design → Build → Deploy seam that GRC and MLOps platforms each stop short of.

Brand examples are illustrative, not endorsements - we compose to whatever stack you already run.

The full tools-by-phase matrix
Every tool in the composed stack - 51 across the nine phases. Filter by function, by phase, or by open-source vs commercial.
Function
Phase
Source
Phase 1
Initiate & scope
Map
VerifyWise
Credo AI
Holistic AI
OneTrust AI Governance
Phase 2
Data & knowledge
Map
Microsoft Presidio
OpenMetadata / DataHub
Qdrant
pgvector / Milvus
DVC / LakeFS
Unity Catalog / Purview / Atlan
Pinecone
Phase 3
Design & architecture
Map
LangGraph
deepagents
MITRE ATLAS
NeMo Guardrails / Guardrails AI / Llama Guard
Lakera
Phase 4
Build
Measure
LangChain
Langfuse (prompt mgmt)
HashiCorp Vault
ModelScan / Semgrep
LangSmith Prompt Hub
Phase 5
Evaluate & test
Measure
deepeval
DeepTeam
Ragas
promptfoo
Arize Phoenix / TruLens
garak / PyRIT
AIF360 / Fairlearn
LangSmith Evaluation
Braintrust
Phase 6
Review & sign-off
Manage
Google Model Card Toolkit
Croissant
Monitaur
IBM watsonx.governance
Phase 7
Deploy & release
Manage
LiteLLM
OpenFGA
LangSmith Deployment / Fleet
LangGraph Platform
Portkey / TrueFoundry
Trust3
Bedrock Guardrails / Azure AI Content Safety
Phase 8
Monitor & observe
Manage
Langfuse
OpenLLMetry
Evidently
LangSmith
Datadog LLM Observability
WhyLabs / Fiddler / Arize
Phase 9
Operate, respond & retire
Manage
MLflow
DeepTeam / garak (scheduled)
LangSmith annotation queues
PagerDuty
Open source Commercial Function colour = NIST AI RMF mapping (Build → Measure, Review → Manage).
The Deliverable

A signed verdict - not a dashboard of numbers.

Observability tools tell you what happened. Neither a trace nor a drift chart is an answer to “show me this system was approved, by whom, against what bar.” That answer is an artifact, and it's what we hand over.

.docx

The Evidence Pack

One per phase, signable. Model card, eval and red-team results, data lineage, threat model, the DPIA where personal data is involved, the go/no-go decision and any conditions attached to it. The document a client's risk team or a regulator can read end to end.

.xlsx

The Living Register

The AI inventory that stays current. Every system, its risk tier, its owner, its gate history, its residual risk, its review dates. The thing an auditor asks for first and most organisations cannot produce.

AI System ID · FCL-AI-0142
Everything joins on one identifier.Each system gets a single AI System ID, and every artifact, gate decision, eval run, trace and register row hangs off it. That's what turns nine separate phases into one auditable thread - and it's the specific thing no GRC platform and no MLOps platform gives you, because each of them only sees half the lifecycle.
Evidence Pack - Phase 6 · Review & sign-off .docx
Evidence Pack · Review & sign-off
AI System ID: FCL-AI-0142 · Claims Triage Copilot · rev 3
Model card
Illustrative model card from a sample Evidence Pack.
PurposeTriage inbound claims & draft a first response
OwnerGovernance, Risk & Legal - J. Meyer
Risk tierHigh (EU AI Act, Annex III)
ModelClaude Sonnet 5 + retrieval, guardrailed
Evaluation summary
Illustrative evaluation results against the defined quality bar.
MetricResultBarPass
Groundedness94%≥ 90%
Prompt-injection resistance98%≥ 95%
Toxicity rate0.08%< 0.5%
Decision: GO - with conditions
Reviewer: A. Okafor (independent) · Risk & Compliance · 2026-06-28 · Condition: human approval on payouts > €5,000.
Living Register - AI inventory .xlsx
Illustrative AI inventory from a sample Living Register.
AI System IDSystemOwnerRisk tierPhaseLast gateResidualNext review
FCL-AI-0142Claims Triage CopilotGRL · MeyerHigh8 · Monitorgo-live ✓Low2026-09-01
FCL-AI-0138Support CopilotPO · NaiduLimited9 · Operatego-live ✓Low2026-08-15
FCL-AI-0151Underwriting AssistantGRL · MeyerHigh5 · Evaluatemeets-the-bar ⧗Med2026-07-22
FCL-AI-0155Marketing Copy GenPO · SilvaMinimal7 · Deploygo-live ✓Low2026-10-01
FCL-AI-0160KYC Doc ExtractorAR · ChenHigh3 · Designdesign-review ⧗-2026-07-18
Get a sample Evidence Pack template
The redacted .docx we hand over - so you have something to put in front of a client who's asking. Score first, gate second.
Thank you! Your submission has been received!
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Sample templates are being finalised with our delivery team - enter your email and we'll send the current redacted pack, or reach us at connect@focaloid.com.

Accountability

Every phase has a named owner. That's the point of a RACI.

“The team is responsible” is how governance fails. Each phase names who is Accountable (one person, the decision), who is Responsible (does the work), and who is Consulted and Informed. Eight roles carry the lifecycle between them.

PO
Product / Business Owner
Accountable for the build decision (Phase 1) and for authorising release (Phase 7).
AR
AI Architect
Accountable for the design (Phase 3) and for build quality (Phase 4).
GRL
Governance, Risk & Legal
Accountable for intake, data sign-off, test adequacy, ongoing oversight and retirement.
ENG
AI / Agent Engineer
Responsible for prototyping and implementing the system.
DAT
Data Engineer / Steward
Responsible for sourcing, cleaning, indexing and versioning every dataset.
QA
Eval / QA Engineer
Responsible for the evals - correctness, groundedness, agent trajectory.
SEC
AI Security / Red Team
Responsible for adversarial testing and leads on incidents.
OPS
MLOps / Platform Engineer
Responsible for deployment, observability and operating the system.
§The independence rule. Phase 6 review is done by people who didn't build it. Sign-off by the builder isn't sign-off.
AAccountable RResponsible CConsulted IInformed

Click a phase row to see who owns it end to end.

RACI matrix: for each of the nine lifecycle phases, which of the eight roles is Accountable, Responsible, Consulted or Informed.
Phase \ Role PO AR GRL ENG DAT QA SEC OPS
1 · Initiate & scopeACRIICI
2 · Data & knowledgeICAIRC
3 · Design & architectureIACRIRC
4 · BuildARCICI
5 · Evaluate & testICACRRI
6 · Review & sign-offCCAIIRCI
7 · Deploy & releaseACIICR
8 · Monitor & observeIIACRCR
9 · Operate, respond & retireICAICRR
Two Ways In

Building new AI, or fixing the AI you already shipped.

Governed by construction

We're building it - the nine phases are the build.

Governance costs almost nothing when it's threaded through from Phase 1 - and the evidence pack assembles itself as you go, because every gate produced one. You ship with the proof already in hand.

Cheapest when it's designed in from the start.
Review-ready, retrofitted

You already shipped - and someone's now asking.

You have AI in production and a customer or regulator is asking questions. We run the lifecycle backwards over what exists - inventory it, risk-tier it, evaluate and red-team it, document it, and close the gaps that matter. You end up with the evidence you should have had.

The fastest way out of a stalled review.
Start Here

A Governance Health Check - turn “trust us” into evidence you can show a client.

A structured, eight-dimension diagnostic of your AI estate. Scored, with a profile of your strengths and gaps and a practical 90-day roadmap. Fixed scope, fast, and it ends with something you can act on rather than a proposal.

01 · Assess
Score eight dimensions
Inventory, risk, data, testing, security, guardrails, monitoring and policy - scored honestly.
02 · Prioritise
A risk-based gap list
Not everything at once - what matters most, first, ranked by risk.
03 · Roadmap
A practical 90-day plan
A plan to close the gaps, and a map to the right engagement level.
Governance maturity - 8-dimension self-check0 / 16 answered
Inventory
We maintain a complete inventory of the AI systems we run.
Every AI system has a named owner and a risk tier.
Risk
New AI use cases are risk-tiered before any build starts.
Each system is mapped to its regulatory obligations (EU AI Act role, etc.).
Data
Every dataset and RAG source has recorded provenance and a lawful basis.
PII is detected and handled before data is indexed or used.
Testing
Systems are evaluated against a defined quality bar before release.
We red-team for prompt injection and the OWASP LLM Top 10.
Security
Agents run with least-privilege, scoped tool permissions.
Irreversible actions require a human approval step.
Guardrails
Input/output guardrails are enforced at runtime, not just in the prompt.
Prompts and model versions are versioned and traceable.
Monitoring
Production systems have tracing on every interaction.
We monitor for quality drift, cost and abuse, with alerts.
Policy
There is a written AI policy and a clear accountability (a RACI).
Go/no-go decisions are documented at defined gates.
Inventory Risk Data Testing Security Guardrails Monitoring Policy
Answer the eight dimensions on the left - your maturity profile builds here as you go.
Get the full report + 90-day roadmap
Your score is yours already. Enter your email and we'll send the written report, benchmarks and a prioritised plan.
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Your score is computed in your browser and shown instantly - nothing is sent until you ask for the full report.

Engagement Levels

Four levels. Start where you are.

Level 1

Assessment & Roadmap

The Health Check, scored, with a prioritised 90-day plan. Where most engagements begin.

Start here
Level 2

Govern one system

Take a single AI system end to end through the nine phases - the full evidence pack and a signed verdict.

Indicative - being finalised
Level 3

Govern the estate

Inventory, policy and a Living Register across every AI system you run - governance as a standing capability.

Indicative - being finalised
Level 4

ISO/IEC 42001 readiness

The full AI management system, prepared for certification against ISO/IEC 42001.

42001-aligned
Who It's For

Built for teams whose AI has to survive someone else's scrutiny.

The EU AI Act applies to us and we don't know what we'd have to show.

An enterprise customer's risk review is holding up the deal.

We shipped AI fast and now we can't evidence any of it.

We have agents taking real actions and no one can say what they did, or why.

Our board asked who is accountable for the AI, and the room went quiet.

We need ISO 42001 or our procurement stalls.

Usually a CTO, VP of Engineering, Head of Risk or Compliance, a DPO, a CISO, or a founder whose deal is stuck in a security questionnaire - in Europe, the UK and the US.

Why Focaloid for Governance

We govern AI because we build it.

A method, not an opinion

Nine phases, eight gates, a RACI and an artifact per phase - proprietary, documented, and mapped to three frameworks. Most firms bring principles. We bring a lifecycle.

Engineers, not auditors

We build agentic systems in production. We know what a guardrail costs, where a trace has to be wired, and why a red-team finding is real - because we've had to fix them.

We close the seam

Our artifact packs span the Design → Build → Deploy gap that GRC and MLOps platforms each stop short of. That's the whole reason the method exists.

Composed, not sold

We don't resell a platform. We compose to whatever stack you already run - and we'll tell you when a tool you already own is enough.

Partners & Certifications
ISO/IEC 27001:2022 CertifiedMember of the Claude Partner NetworkDatabricks PartnerSnowflake Partner
Common Questions

Before you book.

Does the EU AI Act actually apply to us?

If you place AI on the EU market or your output is used there, usually yes - regardless of where you're headquartered. What changes is your role (provider or deployer) and your risk tier, and that classification is exactly what Phase 1 settles.

We're US-based. Is this only a European problem?

No. The NIST AI RMF is becoming the de facto US bar, state laws are arriving, and your enterprise customers' security reviews already ask these questions. The same lifecycle answers all of it.

Will this slow our delivery down?

A gate is a five-minute documented decision, not a committee. Threaded in from Phase 1 the overhead is small - it's the retrofit, after someone asks for evidence you never captured, that's expensive.

Can you govern AI you didn't build?

Yes - that's the review-ready path. We run the lifecycle backwards over what's already in production, and close the gaps that matter.

Do we have to buy a governance platform?

No. We compose to the stack you already run, and we'll tell you when what you own is enough. Our artifact packs are the connective tissue - that's the part no platform sells.

What do we actually walk away with?

A signable Evidence Pack per phase, a Living Register of your AI estate, and a scored maturity profile with a 90-day roadmap. Documents you can hand to a client, an auditor or your board.

How fast is the Health Check?

Fixed scope and fast - you get a scored profile and a prioritised roadmap, not a proposal. It's the cheapest way to find out how exposed you actually are.

The Next Step

Find out how exposed you actually are.

Start with a Governance Health Check - eight dimensions, scored, with a 90-day roadmap out the other side. It's how we turn “trust us” into evidence you can put in front of a client.

Aligned toEU AI Act·NIST AI RMF·ISO/IEC 42001·ISO/IEC 27001:2022 Certified
Start the Health Check