Art. 50(2) marking deadline: 2 Dec 2026 · 58 days

AI decisionsyour board can defend.With the evidence attached.

Quantamix builds the evidence layer under enterprise AI: every output traced to its policy, its data, its model and its approval, so it can be checked by someone who was never in the room. Built in the Netherlands for regulated industries.

TRACE Protocol compliance knowledge graph — animated architecture showing TAMR+, GraQle, EU AI Act, ISO 42001 nodes
€500K+
Saved at Philips
verified, year one
75%
Faster Content Cycles
20 hours down to 5
3
EU Patent Applications
pending at the EPO
PhilipsING BankRabobankAmazon RingDeutsche Bank

New · Free self-assessment

How defensible is your AI under the EU AI Act?

30 governance questions · instant maturity score · risk flags across AI inventory, EU AI Act and GDPR/AVG. No sign-up required.

Start the free scan →15–30 minutes · instant results

The Diagnostic

Five dimensions. One trust score.

TRACE scores every AI decision on Transparency, Reasoning, Auditability, Compliance, and Explainability — so you know exactly how much to trust it.

€35M

Average GDPR fine

GDPR Enforcement Tracker, 2024

85%

AI projects never reach production

Gartner Predicts, 2024

73%

Organizations failing audit readiness

A-LIGN/ISACA, 2025

The TRACE diagnostic

TRACETRACE
  • TTransparency— Decisions made visible
  • RReasoning— Logic you can trace
  • AAuditability— Proof that survives
  • CCompliance— Regulation-ready always
  • EExplainability— AI anyone understands

Three challenges. One connected approach.

01

Content at scale. Brand intact.

Enterprise teams manage 500K+ assets. Knowledge workers lose 60% of time to process overhead.

Philips: 20 hours → 5 hours per product line. 95% brand compliance. €500K saved year one.

TRACE
CrawlQ.aiStudio CrawlQ.aiCopyNexus.io

Forrester TEI, 2023; Adobe State of Work, 2023

02

Compliance you can prove.

EU AI Act high-risk Annex III obligations apply from 2 Dec 2027 (postponed from Aug 2026 by Regulation (EU) 2026/1744, Digital Omnibus on AI, in force 27 July 2026). Article 50 transparency applies since 2 Aug 2026; generative AI already on the market must meet the Art. 50(2) output-marking duty by 2 Dec 2026, when the nudifier ban also takes effect. Conformity assessment still takes 12–18 months.

Cited, traceable answers on regulatory questions. Patent-pending. Cryptographic proof trail.

TRACE
TraceGov.aiGraqle

Official Journal of the EU, 2024; SSRN 6359818

03

AI pilots that actually ship.

85% of AI initiatives never reach production. The barriers are organizational, not technical.

95 friction points mapped across 8 layers. Compound failure triggers identified. Diagnostic-first.

TRACE
FrictionMelt

Gartner Predicts, 2024; McKinsey State of AI, 2024

All six products share one Knowledge Graph — when one learns, all benefit.

Architecture

Three problems. One intelligence layer.

Content, compliance and AI adoption — connected by a graph reasoning engine that sits between your AI models and your business decisions. EU-resident. Patent-pending. Model-agnostic.

Content

Knowledge that answers questions

CrawlQ.ai · Studio CrawlQ.ai · CopyNexus.io

75% faster · €500K saved

at Philips

Compliance

Decisions that survive an audit

TraceGov.ai · GraQle · TRACE Scoring

graph retrieval

EU AI Act ready

Adoption

Adoption that’s measurable

FrictionMelt · Friction Intelligence

95 friction points

8 org layers mapped

Graph Intelligence Layer

Model-agnostic · EU-first · Patent-pending · Source-available SDK

TAMR+ · GraQle · T·R·A·C·E

Every output is scored across 5 dimensions

T
R
A
C
E

Transparency · Reasoning · Auditability · Compliance · Explainability

Any AI modelOpenAI · Claude · Llama · Mistral · AWS Bedrock · Azure · On-Premise
EU-Built & HeadquarteredPatent pending · EP26162901.8AWS Frankfurt (eu-central-1)Source-available SDK on PyPI

The Platform

One platform. Three pillars.

Intelligence, execution and governance — connected on a shared Knowledge Graph. When one product learns, all benefit.

1

Intelligence

The data foundation

2

Execution

The action layer

3

Governance

The trust layer

CrawlQ.ai logo

CrawlQ.ai

The World's First Content ERP

1 · Intelligence

“You don't know your audience. You think you do.”

Philips cut 20 hours to 5 per product line, saved €500K in year one. CrawlQ turns scattered content into managed capital with 140+ psychographic factors and full audit trail.

  • 75% faster content cycles (Philips, verified)
  • 2,800+ users including Fortune 500
  • 95% brand compliance at scale

2,800+ users | 4.4★ Capterra

G

GraQle

The Intelligence Engine

1 · Intelligence

“Your data knows the answer. Your tools don't.”

The Knowledge Graph connecting all six products. Multiple AI agents cross-check each other on governance questions. Source-available SDK on PyPI.

  • Multi-agent cross-verification
  • Zero LLM calls at retrieval
  • Source-available: 2,009 tests, 201 skills
C

CopyNexus.io

AI Copywriting at Scale

2 · Execution

“Great products fail with bad copy. Great copy fails without brand voice.”

Enterprise copy automation born from real production at Amazon Ring. Thousands of brand-consistent descriptions, social posts, and listings in minutes.

  • Battle-tested at Amazon Ring
  • Multi-channel: web, social, marketplace
  • Connected to CrawlQ audience intelligence
FrictionMelt logo

FrictionMelt

AI Friction Intelligence

2 · Execution

“The best software in the world fails for one reason. People stop using it.”

Your AI pilots work. Enterprise rollout stalls. FrictionMelt diagnoses exactly why: 95 friction points across 8 organizational layers with compound failure analysis.

  • 95 friction points across 8 layers
  • Compound failure trigger identification
  • Prioritized by business impact
TraceGov.ai logo

TraceGov.ai

AI Compliance You Can Prove

3 · Governance

“Every decision your organization makes — can it survive an audit tomorrow?”

Know your exact EU AI Act compliance score today. Scores across 5 TRACE dimensions (Transparency, Reasoning, Auditability, Compliance, Explainability) with 2x the accuracy of standard AI.

  • Graph-based retrieval over the regulatory text
  • Patent-pending (EP26162901.8)
  • Cryptographic audit trail — 7 year retention
Studio CrawlQ.ai logo

Studio CrawlQ.ai

Brand Intelligence Platform

3 · Governance

“Your brand is being misrepresented right now. You just can't see it yet.”

Quantified Brand Trust Score, automatic deviation detection before publication, and AI-generated brand-compliant campaigns. Connected via shared Knowledge Graph.

  • Real-time Brand Trust Score
  • Deviation detection before publication
  • Shared Knowledge Graph with CrawlQ.ai

The Intelligence Engine

GraQle turns codebases into reasoning networks

One knowledge graph. Multiple AI agents that cross-verify each other. Every answer comes with a confidence score and an audit trail. Source-available SDK on PyPI.

Before GraQle: 60 scattered files, 50,000 tokens, 2 minutes. After GraQle: Knowledge graph with 8 agents, 500 tokens, 5.2 seconds, 92% confidence.

Turn any codebase into a reasoning network

Graph-of-agents architecture. Each node becomes an AI agent. They cross-verify before answering.

  • Impact analysis before any code change
  • Cross-project dependency tracing
  • Automated knowledge graph from git history
500tokens

vs 50,000 — 100x cheaper per query

5.2sec

Average reasoning time (was 2 min)

92%

Confidence scoring on every answer

Real stories from production

100xcost reduction
Before

Reading 60 files. 50,000 tokens. 2 minutes. "I think auth is used by..."

After

8 agents activated. 500 tokens. 5.2 seconds. 92% confidence. 11 modules mapped.

GraQle turned a 2-minute guessing exercise into a 5-second verified answer — 100x cheaper, 24x faster.

2,900%info density gain
Before

Neptune had embeddings stored from TAMR+ — but nobody was calling them at retrieval time.

After

Graqle's audit caught what 200+ commits missed. 2,900% more information, same token budget.

The infrastructure existed. The wiring didn't. GraQle found the gap in 0.2 seconds.

1,045issues found
Before

Website passed manual QA. Google Lighthouse showed green. Team approved for launch.

After

SCORCH found 807 jargon terms, 218 ghost elements, and a CTA with 3.68 contrast ratio.

You can't audit what you can't see. GraQle saw 1,045 friction points in 90 seconds.

Trusted by enterprise teams worldwide

PhilipsHealthcare
Amazon RingConsumer Tech
ING BankBanking
RabobankBanking
ASN BankBanking
EYAdvisory
Deutsche BankBanking
Reserve Bank of IndiaCentral Bank

The Engine

TAMR+

Trust-Aware Multi-Signal Document Retrieval — patent-pending retrieval that understands the structure of regulations: articles, recitals, cross-references, not just keywords.

European Patent Application (pending)
EP26162901.8 · 18 claims
Working paper
SSRN 6359818
Paper record
Zenodo 18929634
Source-available
Apache 2.0 · PyPI
TAMR+Trust-Aware RetrievalEP26162901.8TRACEFive-dimension evidence score0LLM calls at retrievalRETRIEVALTAMR+ — Trust-aware multi-signal searchREASONINGGraQle — Graph-of-agents cross-checkingPROOFTRACE — Cryptographic audit trail

What this means for your organization

For the Board

Patent-pending IP means your investment is in original technology, not a wrapper.

For Compliance

Every AI output has a complete proof trail. When an auditor asks how a decision was reached, the system shows them — article by article. 7-year cryptographic retention.

For IT / Security

Works with any AI model — on-premise, cloud, or hybrid. No vendor lock-in. Full data sovereignty. EU-built, EU-headquartered.

Source-available. Verifiable. On PyPI.

Apache 2.0v0.29 · Production/Stable

GraQle SDK

Graph-of-agents reasoning engine. 2,009 tests, 201 skills, 14 LLM backends.

Apache 2.0Standalone Python package

TAMR+ Lite

Trust-aware multi-signal document retrieval. The engine behind TraceGov.ai.

Security & Compliance

EU-first. Sovereign by design.

Your data never leaves Frankfurt. No US data transfer. No CLOUD Act exposure. Built by a European company for European institutions.

Full security documentation: tracegov.ai/security

0US Data Transfers
14Encrypted DynamoDB Tables
7 yrAudit Trail Retention
6Compliance Frameworks

Data Residency

AWS Frankfurt (eu-central-1) exclusively

Zero US data transfer. Zero CLOUD Act exposure.

Encryption at Rest

AES-256 via AWS KMS

14 DynamoDB tables + Neo4j Knowledge Graph, all encrypted.

Encryption in Transit

TLS 1.3 enforced

All data in motion protected with latest transport layer security.

Merkle-Chain Audit Trail

SHA-256 hash-verified records

Cryptographic linking between records. 7 years retention.

Regulatory Compliance

6 frameworks. Real status. No marketing fluff.

  • GDPRAligned

    Articles 5, 25, 28, 32, 35, 44-49

    Data protection by design. Consent-gated analytics. No cross-border transfer outside EU.

  • EU AI ActReady

    Articles 9, 12, 13, 14, 26

    Risk management, record-keeping, transparency, human oversight, and deployer obligations.

  • SOC 2 Type IIIn Progress

    Security, availability, and confidentiality controls under independent audit.

  • ISO 27001Aligned

    Information security management system aligned with international standards.

  • NIS2 DirectiveAligned

    Network and information security measures for essential and important entities.

  • DORAAligned

    Digital operational resilience for financial sector ICT risk management.

Access Control

  • Role-Based Access Control

    Granular permissions per workspace, per user, per action.

  • Multi-Factor Authentication

    MFA enforced for all accounts. No exceptions.

  • Least-Privilege IAM

    Every Lambda, every service, every role — minimum permissions only.

Transparency & AI Ethics

  • No Foundation Model Training

    Your prompts and responses are never used to train foundation models. Your regulatory data stays yours.

  • Honest Benchmarks

    We publish our real TRACE scores -- 60-67%, not >90%. Regulatory AI is hard. We measure honestly and improve transparently.

  • EU-First

    Quantamix Solutions is an EU-based company building sovereign AI infrastructure. Data residency, compliance, and transparency are not features -- they are foundations.

AWS stack, data flow, incident-response SLA and secure-development practicesShow details

Enterprise-Grade AWS Infrastructure

Full stack deployed in AWS Frankfurt (eu-central-1)

Compute & Delivery

  • AWS Lambda — serverless, auto-scaling
  • AWS Amplify — frontend + CI/CD
  • CloudFront CDN — TLS 1.3 enforced
  • Route 53 — DNSSEC-ready DNS
  • WAF — DDoS protection, rate limiting

AI & Data

  • AWS Bedrock — EU inference profiles only
  • DynamoDB — 14 tables, AES-256 encrypted
  • Neo4j — knowledge graph, encrypted
  • S3 — document storage, encrypted
  • TRACE + CERI engines — custom AI scoring

Identity & Monitoring

  • AWS Cognito — MFA, JWT, token rotation
  • IAM — least-privilege, role-based
  • CloudWatch — real-time monitoring
  • Automated anomaly alerting
  • Stripe — PCI DSS Level 1, EU processing

Data Flow — Everything Stays in Frankfurt

Client Browser→ TLS 1.3 →→CloudFront CDN→Amplify + Lambda→Bedrock AI→DynamoDB + Neo4j

All services configured to eu-central-1 via IAM policies, VPC config, and service endpoints.

Incident Response SLA

MinutesDetection (automated)
<1 hourAcknowledgment
<4 hoursContainment
<24 hoursCustomer notification

Secure Development Practices

  • Infrastructure as Code (AWS CDK/CloudFormation)
  • Automated dependency vulnerability scanning
  • Code review required for all production changes
  • Separate staging and production environments
  • Zero third-party data sharing

Responsible Disclosure

Security researchers can report vulnerabilities via security@tracegov.ai.

24h

Acknowledgment

72h

First update on resolution

Full security documentation and Data Processing Agreements available for enterprise customers upon request.

Founder

Built by someone who has sat in your chair

After 18+ years building AI for large, regulated organizations, Harish started Quantamix to help businesses implement practical AI — without lengthy projects or unnecessary complexity.

Strategic AI Advisor to Enterprise Leaders | Architecting GenAI Transformation & Adoption Roadmaps for Fortune 500 & Financial Institutions

Harish Kumar — Founder & CEO, Quantamix Solutions

Harish Kumar

Founder & CEO

Quantamix Solutions B.V.

Uithoorn, Netherlands
European patent application EP26162901.8 (pending)

Credentials

FRMPMPGCPAzureCSMGC

Over 20+ years, Harish has gone from the Reserve Bank of India to Amazon, Deutsche Bank to Philips — always sitting in the same chair as the people he now serves: enterprise leaders navigating AI transformation under real-world constraints. His technical depth spans LLM fine-tuning, Knowledge Graphs, SHACL/OWL ontologies, and end-to-end AWS deployment pipelines.

Key Achievements

500K EUR
Annual savings at Philips through GenAI automation
400B+ EUR
Loan portfolio managed at Rabobank
500+
Enterprise employees trained on AI workflows
200+
GenAI Champions Community at Philips

Enterprise Experience

  • Amazon2024-present

    GenAI transformation for Ring marketing; managed 2,500+ digital assets, 50% efficiency boost.

  • Philips Personal Health2022-2025

    Founded 200-member GenAI Champions Community, 500K EUR annual savings, 80-99% metadata accuracy.

  • ING2025

    Led Google Cloud Migration — Trading Book Stress Testing to GCP using Looker and BigQuery.

  • Rabobank2018-2021

    Product Owner IFRS9 Calculation Engine, managed 400B+ EUR loan portfolio.

  • Deutsche Bank2016-2017

    FRTB and IRRBB Capital Calculations Workstream Lead.

  • ING Nederland2013-2015

    Economic Capital Modeling, regulatory stress testing.

  • Reserve Bank of India2004-2010

    Quantitative Risk Management.

Enterprise Proof

Results from the people who used it

A Fortune 500 case study, verified user reviews and the numbers behind them.

“CrawlQ's AI platform shifted my perspective on what AI can offer at enterprise level.”
Richard Taylor
Strategic Copywriter, Philips Personal Health

20h→5h per product line · 500+ SKUs · 60% cost reduction

Philips

Philips Personal Health

Fortune 500 — Healthcare Technology

75%
Faster content cycles
95%
Brand compliance
500+
SKUs supported
€500K
Saved in year one
“Other tools tell us what audience searches for; CrawlQ tells us what it wants. When we know what it wants, we can write content accordingly.”
Zohaib Salman
Writer, Punjab Bar Council
“Its market research is even more in depth than a professional market research audit.”
Valor L.
Digital Strategist
425%
Average ROCC returns
83%
Average first-year ROI
2,800+
Users across 40+ countries
148+
Verified reviews
  • 4.4/5on Capterra (45)
  • 4.5/5on AppSumo (101)
  • 5.0/5on Trustpilot (2)

EU AI Act · Regulation (EU) 2024/1689

Article 50 already applies. High-risk comes next.

Article 50 transparency obligations apply since 2 August 2026; generative AI systems placed on the market before that date must meet the Art. 50(2) output-marking duty by 2 December 2026, the same day the nudifier ban takes effect. The Regulation (EU) 2026/1744 (Digital Omnibus on AI) moved high-risk obligations to 2 December 2027 (Annex III) and 2 August 2028 (Annex I products).

Regulation (EU) 2024/1689 amended by Regulation (EU) 2026/1744, Digital Omnibus on AI, in force 27 July 2026.

Countdown · Art. 50(2) output marking

00
Days
:
00
Hours
:
00
Min

Art. 50(2) output-marking deadline for generative AI already on the market, 2 December 2026 (nudifier ban takes effect 2 December 2026).

Article 50 / Article 99(4) penalties: up to €15M or 3% of global annual turnover · Read the Omnibus breakdown →

  1. 01in force

    2 August 2026

    Article 50 in force

    Disclosure, deepfake labelling and output-marking obligations apply. Not delayed by the Omnibus.

  2. 02upcoming

    2 December 2026

    Output marking · nudifier ban

    Generative AI already on the market must meet the Art. 50(2) output-marking duty. The nudifier ban takes effect 2 December 2026.

  3. 03upcoming

    2 December 2027

    was Aug 2026

    Annex III high-risk

    Conformity assessment, technical documentation and risk management for Annex III high-risk systems.

  4. 04upcoming

    2 August 2028

    was Aug 2027

    Annex I products

    AI embedded in regulated products (medical devices, machinery delegated acts, automotive).

Start your compliance assessment

Get a free EU AI Act readiness report for your organization. A 30-minute assessment gives you a clear picture of where you stand.

EU-built. EU-headquartered. Your data stays in Frankfurt (eu-central-1). No vendor lock-in.

Common Questions

Every objection. Answered with evidence.

From integration fears to board approval blockers - these are the real questions enterprises ask before implementing EU AI Act compliance as middleware.

T·R·A·C·E

Middleware - not a replacement.

TRACE sits between your existing AI platform (Microsoft Copilot, AWS Bedrock, Google Vertex AI, OpenAI, SAP) and your compliance outputs. Your operations continue unchanged. TRACE adds the compliance wrapper, audit trail, and regulator-ready reports - in as little as 2 days via API gateway. Three pending patent applications. Published benchmarks. 14 days to first evidence output.

INTEGRATIONDo we need to replace our existing AI systems - Microsoft Copilot, AWS Bedrock, Google Vertex AI?

No. TRACE is a middleware layer that sits between your existing AI platform and your outputs. Your systems continue running exactly as today. TRACE intercepts outputs, wraps them with the compliance layer, generates the audit trail, and returns the result with its audit record. Three integration patterns: (1) API Gateway - route AI outputs through the TRACE endpoint, zero code changes to your existing system, live in 2 days. (2) SDK wrapper - 3 lines of code around your existing LLM client, live in 1 week. (3) Async audit pipeline - your AI runs normally and TRACE processes outputs asynchronously, live in 2 weeks. No vendor lock-in. Works with any AI system that produces text output.

Plug-and-play

MYTHWe already have Microsoft/AWS/Google compliance tools. Aren't we covered?

No. Hyperscalers provide infrastructure compliance - SOC 2, ISO 27001, GDPR data processing agreements. They do not provide EU AI Act compliance. Microsoft Responsible AI Toolkit is a framework, not a conformity system. AWS AI compliance covers data security. Google Vertex AI has no EU AI Act conformity output. None of them produce Art 13 audit logs, Art 17 quality management system evidence, conformity assessment documentation, or a TRACE score. TRACE fills the gap that every hyperscaler leaves open - because it is a regulatory problem, not an infrastructure problem.

Myth busted

MYTHOur AI system is low-risk. The EU AI Act doesn't apply to us.

Under Article 6, the following are classified HIGH-RISK by default: AI used in financial services (credit scoring, fraud detection, AML monitoring), HR (CV screening, performance management, workforce planning), legal (contract review, compliance checking), healthcare (diagnostic support, triage), and any AI influencing access to essential services. If you use Copilot, Bedrock, or any LLM for any of these use cases, you are in scope. Annex III conformity assessment obligations apply to you from 2 December 2027 (Regulation (EU) 2026/1744, Digital Omnibus on AI, in force 27 July 2026). GPAI obligations - which cover any general-purpose AI model - are already active since August 2025, and Article 50 transparency obligations since 2 August 2026.

High-risk check

DATAWhat about data sovereignty and GDPR? We cannot send data to a third party.

TRACE runs entirely in AWS eu-central-1 (Frankfurt). Your data never leaves the EU. Critically, TRACE processes AI OUTPUTS - the text responses from your AI system - not the personal data that generated those outputs. This means GDPR data subject rights do not apply to the compliance processing layer. We provide: a Data Processing Agreement (Art 28 GDPR), EU Standard Contractual Clauses, explicit data residency commitments, and a right-to-audit clause. For organisations with sovereign cloud requirements, we also support deployment into your own AWS EU account.

EU data residency

PROCESSWe need board approval. This will take months internally.

TRACE generates a board-ready TRACE score report in 6 hours - showing your current compliance gap across all five TRACE properties, the exact EUR fine exposure you face based on your AI system inventory, and the ROI case for remediation. We have seen this compress board approval cycles from months to weeks because the report makes the risk concrete, quantified, and boardroom-legible. We offer this as a pre-approval diagnostic: no commitment, no cost, just evidence. You walk into the board meeting with a EUR-quantified risk assessment rather than an abstract regulatory summary.

6-hr board report

TIMELINEHow long until we are actually compliant? We have a deadline.

Weeks 1-2: Discovery and TRACE baseline - we inventory your AI systems, classify risk, run the first TRACE score. Weeks 3-6: TAMR+ integration - regulatory corpus ingested, multi-agent reasoning live, first benchmark validated. Weeks 7-10: GraQle live - real-time gap detection active, knowledge graph populated, audit trail running. Weeks 11-13: Evidence pack ready - documentation designed to support an ISO 42001 audit and EU AI Act conformity assessment, board presentation prepared. First evidence output: 14 days. Whether you are compliant, and any certification, is decided by your own assessment, your auditors or a notified body - not by TRACE. GPAI obligations (active since August 2025) addressed in the first 2-week sprint.

14 days first output

COSTWe cannot afford this right now. Budget is frozen.

The cost of non-compliance is EUR 35 million or 7% of global annual turnover - whichever is higher - plus reputational damage, forced system shutdowns, and operational disruption. The average TRACE implementation saves EUR 570K in Year 1 through eliminated external compliance consultancy, faster regulatory change response (8.5x), and avoided fines. ROI is 4.6x in Year 1. If your annual global turnover is above EUR 100M, your maximum exposure is EUR 7M+. The question is not whether you can afford TRACE. It is whether you can afford the EUR 35M alternative.

4.6x ROI Year 1

AUDITWhat actually happens during a real EU AI Act audit? What will regulators ask for?

Regulators request five things: (1) Evidence that your AI systems were correctly classified under Article 6 - high-risk vs limited-risk vs minimal-risk. (2) Logs of every AI decision with human oversight records per Article 13. (3) A conformity assessment or technical documentation demonstrating the system meets Act requirements. (4) A quality management system showing ongoing monitoring, as required by Article 17. (5) Post-market surveillance data. Without TRACE, producing this takes 3-6 weeks and typically surfaces gaps. With TRACE, you export the full evidence pack in under 6 hours. The TRACE score is your pre-audit readiness indicator - if it is above 0.75, you are audit-ready.

Audit-ready in 6hrs

TEAMWe already have a legal and compliance team. Why do we need TRACE?

Manual compliance processing takes 23 hours per regulatory change event. The EU AI Act has already generated hundreds of guidance updates, national transpositions, and GPAI Code of Practice iterations since its entry into force - and enforcement has not yet started. TRACE does not replace your compliance team. It makes them 8.5x more effective by automating evidence collection, gap detection, and report generation. Your team focuses on judgment calls, stakeholder management, and remediation decisions. TRACE handles the evidence chain, the regulatory mapping, and the audit trail that would otherwise consume weeks of their time.

8.5x team efficiency

POCCan we start with a proof of concept before committing?

Yes - and we recommend it. Standard POC: 2 weeks, one AI system, full TRACE score report delivered at the end. You see exactly where your gaps are across all five TRACE properties, what the remediation roadmap looks like, and what your projected timeline to full compliance is. No commitment required after the POC. Most organisations convert because the TRACE score report creates internal urgency that abstract risk assessments never do - it shows the gap in a board-legible, EUR-quantified, deadline-mapped format. The POC itself typically produces enough evidence to secure budget approval internally.

2-week no-commitment POC

Still have a question not covered here? Book a 60-minute diagnostic call - we will answer everything specific to your stack.

Book Your Diagnostic Call

The GraQle Podcast

Agentic AI you can trust — in plain language

Two short-form series. Governed Memory — agent memory as a governed reasoning substrate. GraQle for Finance — deep agentic AI for the teams under the CFO who close the books.

Contact

Let's talk about what you're building

Whether you're evaluating AI compliance tools, planning an enterprise AI rollout, or navigating the EU AI Act — we are happy to help. We respond within 24 hours. No obligations, no sales pressure.

Company

Quantamix Solutions B.V.

KVK: 73625183

Buitendijks 2, 1422MM

Uithoorn, Netherlands