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Audited and Certified

With Human First - AI Regulatory Framework


Our Services

The Standard in AI Certification

We provide independent, human-first AI certification, ensuring every system is safe, reliable, and accountable so companies can innovate with confidence and humans can trust the technology that shapes their world.

All Tasks

Waiting for approval

  • Review Docs

    Model Cards, Terms, Privacy Policies

  • External Audit

    Test AI Behavior and Outputs

  • HF-1 Certification

    Certification for Compliant Systems

  • Reporting & Transparency

    Verified Reports to Build Trust

  • Next-Gen Compliance

    Ensure Audit Evolves for Safety

All Tasks

Waiting for approval

  • Review Docs

    Model Cards, Terms, Privacy Policies

  • External Audit

    Test AI Behavior and Outputs

  • HF-1 Certification

    Certification for Compliant Systems

  • Reporting & Transparency

    Verified Reports to Build Trust

  • Next-Gen Compliance

    Ensure Audit Evolves for Safety

All Tasks

Waiting for approval

  • Review Docs

    Model Cards, Terms, Privacy Policies

  • External Audit

    Test AI Behavior and Outputs

  • HF-1 Certification

    Certification for Compliant Systems

  • Reporting & Transparency

    Verified Reports to Build Trust

  • Next-Gen Compliance

    Ensure Audit Evolves for Safety

HF-1 Certification

No Data Leaks For You

Every AI system we certify undergoes rigorous human-first reviews and external audits. Every document checked. Every output verified. Every process scrutinized. Your data remains private, secure, and fully protected giving companies confidence and users peace of mind.

External Audit Task

Trusted Standards

Model Interaction

We Study How AI Behaves

AI doesn't just answer, they influence. We surface where models misleads, leak sensitive data, or make harmful decisions so organizations can fix them before people get hurt

Tone & Manipulation

Context Failure

Human Impact Assessment

What can I help with?

Weather you want help in customer handling or make changes in your system just give me command

|

Add document

Analyze

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research

What can I help with?

Weather you want help in customer handling or make changes in your system just give me command

|

Add document

Analyze

Generate Image

research

What can I help with?

Weather you want help in customer handling or make changes in your system just give me command

|

Add document

Analyze

Generate Image

Risk Found | Alerting

LinkedIn

IT services

Founders

Draft

Schedule

Sent

Risk Found | Alerting

LinkedIn

IT services

Founders

Draft

Schedule

Sent

Risk Found | Alerting

LinkedIn

IT services

Founders

Draft

Schedule

Sent

Risk Alerting

Alerts When Risks Are Found

When our audits uncover potential risks in messaging or AI systems, as well as terms and policies, we ensure the right people are notified immediately. Our process helps companies respond quickly mitigate issues and maintain trust.

Compliance Officers

Team Leads & Managers

Customers

Tailored Audits

People Over Systems

Every organization is different, but our focus is always on the human impacted by AI. We design tailored audits and certification processes that keep people safe

Strategy

Custom AI

Consulting

LumosAI

Tailored Audit - Cert. Pending

On going project :

Customer Support Chatbot

90% Finsihed

Schedule

Mo

Tu

We

Th

Fr

Sa

Su

Risk team call

10:00 am to 10:30 am

Audit

06:00 pm to 06:30 pm

LumosAI

Tailored Audit - Cert. Pending

On going project :

Customer Support Chatbot

90% Finsihed

Schedule

Mo

Tu

We

Th

Fr

Sa

Su

Risk team call

10:00 am to 10:30 am

Audit

06:00 pm to 06:30 pm

LumosAI

Tailored Audit - Cert. Pending

On going project :

Customer Support Chatbot

90% Finsihed

Schedule

Mo

Tu

We

Th

Fr

Sa

Su

Risk team call

10:00 am to 10:30 am

Audit

06:00 pm to 06:30 pm

Our Process

Our Simple, Smart, and Human First Process

Our HF-1 framework is designed to audit, certify, monitor AI systems with minimal disruption protecting people, ensuring accountability, and building trust in AI

Step 1

Smart Analysis

We assess your AI systems and workflows to identify risks, compliance gaps, and areas where human-first safeguards are needed

Analyzing current workflow..

System check

Process check

Bias check

Data Privacy Control

Repeated

Analyzing current workflow..

System check

Process check

Bias check

Data Privacy Control

Repeated

Step 2

Risk Evaluation

Our team conducts throughout audits to evaluate AI outputs, interactions, and decision patterns ensure every system meets HF-1. standards.

  • # HF-1 Risk Eval • Readable, non-functional mockup

    def load_sample_interactions(batch_size=50):
        """Load representative prompts, messages, and system outputs."""
        return [
            {"id": "u001", "input": "Explain X to a child", "output": "..."},
            {"id": "u002", "input": "Hire a driver from Y", "output": "..."},
            # ... sample set ...
        ][:batch_size]

    def analyze_output(output):
        """Run layered checks and return a risk profile (mock)."""
        profile = {
            "toxicity_score": round(0.0 + hash(output) % 100 / 100, 2),
            "bias_signals": ["gender"] if "she" in output.lower() else [],
            "privacy_flags": ["possible-pii"] if "email@" in output else [],
            "explainability": "low" if "because" not in output else "high"
        }
        return profile

    def aggregate_findings(samples):
        """Aggregate per-sample profiles into a human-review dashboard."""
        findings = []
        for s in samples:
            p = analyze_output(s["output"])
            findings.append({
                "sample_id": s["id"],
                "input": s["input"],
                "risk_profile": p,
                "recommended_action": (
                    "manual review" if p["toxicity_score"] > 0.6 or p["privacy_flags"] else
                    "monitor"
                )
            })
        return {"summary": {"total": len(findings), "high_risk": len([f for f in findings if f["recommended_action"] == "manual review"])}, "items": findings}

    def generate_report(aggregated):
        """Produce human-readable findings for stakeholders (mock)."""
        report = {
            "title": "HF-1 Risk Evaluation — Summary",
            "summary": aggregated["summary"],
            "notes": "This report highlights outputs requiring human review and areas for mitigation.",
            "items_preview": aggregated["items"][:5]
        }
        return report

    # ---- execution (illustrative only) ----
    samples = load_sample_interactions(100)
    aggregated = aggregate_findings(samples)
    report = generate_report(aggregated)

    # Print (mock) output shown to auditors
    print(report)
    # ----------------------------------------
  • # HF-1 Risk Eval • Readable, non-functional mockup

    def load_sample_interactions(batch_size=50):
        """Load representative prompts, messages, and system outputs."""
        return [
            {"id": "u001", "input": "Explain X to a child", "output": "..."},
            {"id": "u002", "input": "Hire a driver from Y", "output": "..."},
            # ... sample set ...
        ][:batch_size]

    def analyze_output(output):
        """Run layered checks and return a risk profile (mock)."""
        profile = {
            "toxicity_score": round(0.0 + hash(output) % 100 / 100, 2),
            "bias_signals": ["gender"] if "she" in output.lower() else [],
            "privacy_flags": ["possible-pii"] if "email@" in output else [],
            "explainability": "low" if "because" not in output else "high"
        }
        return profile

    def aggregate_findings(samples):
        """Aggregate per-sample profiles into a human-review dashboard."""
        findings = []
        for s in samples:
            p = analyze_output(s["output"])
            findings.append({
                "sample_id": s["id"],
                "input": s["input"],
                "risk_profile": p,
                "recommended_action": (
                    "manual review" if p["toxicity_score"] > 0.6 or p["privacy_flags"] else
                    "monitor"
                )
            })
        return {"summary": {"total": len(findings), "high_risk": len([f for f in findings if f["recommended_action"] == "manual review"])}, "items": findings}

    def generate_report(aggregated):
        """Produce human-readable findings for stakeholders (mock)."""
        report = {
            "title": "HF-1 Risk Evaluation — Summary",
            "summary": aggregated["summary"],
            "notes": "This report highlights outputs requiring human review and areas for mitigation.",
            "items_preview": aggregated["items"][:5]
        }
        return report

    # ---- execution (illustrative only) ----
    samples = load_sample_interactions(100)
    aggregated = aggregate_findings(samples)
    report = generate_report(aggregated)

    # Print (mock) output shown to auditors
    print(report)
    # ----------------------------------------
  • # HF-1 Risk Eval • Readable, non-functional mockup

    def load_sample_interactions(batch_size=50):
        """Load representative prompts, messages, and system outputs."""
        return [
            {"id": "u001", "input": "Explain X to a child", "output": "..."},
            {"id": "u002", "input": "Hire a driver from Y", "output": "..."},
            # ... sample set ...
        ][:batch_size]

    def analyze_output(output):
        """Run layered checks and return a risk profile (mock)."""
        profile = {
            "toxicity_score": round(0.0 + hash(output) % 100 / 100, 2),
            "bias_signals": ["gender"] if "she" in output.lower() else [],
            "privacy_flags": ["possible-pii"] if "email@" in output else [],
            "explainability": "low" if "because" not in output else "high"
        }
        return profile

    def aggregate_findings(samples):
        """Aggregate per-sample profiles into a human-review dashboard."""
        findings = []
        for s in samples:
            p = analyze_output(s["output"])
            findings.append({
                "sample_id": s["id"],
                "input": s["input"],
                "risk_profile": p,
                "recommended_action": (
                    "manual review" if p["toxicity_score"] > 0.6 or p["privacy_flags"] else
                    "monitor"
                )
            })
        return {"summary": {"total": len(findings), "high_risk": len([f for f in findings if f["recommended_action"] == "manual review"])}, "items": findings}

    def generate_report(aggregated):
        """Produce human-readable findings for stakeholders (mock)."""
        report = {
            "title": "HF-1 Risk Evaluation — Summary",
            "summary": aggregated["summary"],
            "notes": "This report highlights outputs requiring human review and areas for mitigation.",
            "items_preview": aggregated["items"][:5]
        }
        return report

    # ---- execution (illustrative only) ----
    samples = load_sample_interactions(100)
    aggregated = aggregate_findings(samples)
    report = generate_report(aggregated)

    # Print (mock) output shown to auditors
    print(report)
    # ----------------------------------------
  • # HF-1 Risk Eval • Readable, non-functional mockup

    def load_sample_interactions(batch_size=50):
        """Load representative prompts, messages, and system outputs."""
        return [
            {"id": "u001", "input": "Explain X to a child", "output": "..."},
            {"id": "u002", "input": "Hire a driver from Y", "output": "..."},
            # ... sample set ...
        ][:batch_size]

    def analyze_output(output):
        """Run layered checks and return a risk profile (mock)."""
        profile = {
            "toxicity_score": round(0.0 + hash(output) % 100 / 100, 2),
            "bias_signals": ["gender"] if "she" in output.lower() else [],
            "privacy_flags": ["possible-pii"] if "email@" in output else [],
            "explainability": "low" if "because" not in output else "high"
        }
        return profile

    def aggregate_findings(samples):
        """Aggregate per-sample profiles into a human-review dashboard."""
        findings = []
        for s in samples:
            p = analyze_output(s["output"])
            findings.append({
                "sample_id": s["id"],
                "input": s["input"],
                "risk_profile": p,
                "recommended_action": (
                    "manual review" if p["toxicity_score"] > 0.6 or p["privacy_flags"] else
                    "monitor"
                )
            })
        return {"summary": {"total": len(findings), "high_risk": len([f for f in findings if f["recommended_action"] == "manual review"])}, "items": findings}

    def generate_report(aggregated):
        """Produce human-readable findings for stakeholders (mock)."""
        report = {
            "title": "HF-1 Risk Evaluation — Summary",
            "summary": aggregated["summary"],
            "notes": "This report highlights outputs requiring human review and areas for mitigation.",
            "items_preview": aggregated["items"][:5]
        }
        return report

    # ---- execution (illustrative only) ----
    samples = load_sample_interactions(100)
    aggregated = aggregate_findings(samples)
    report = generate_report(aggregated)

    # Print (mock) output shown to auditors
    print(report)
    # ----------------------------------------

Step 3

Seamless Certification

We verify AI systems with clear documentation, integrating our certification without disruptions

Our solution

Your stack

Our solution

Your stack

Step 4

Continuous Oversight

We refine and monitor over time, analyzing results, mitigating public risks and updating certification to ensure long term safety

Chatbot system

Efficiency will increase by 20%

Workflow system

Update available..

Sales system

Up to date

Chatbot system

Efficiency will increase by 20%

Workflow system

Update available..

Sales system

Up to date

Case Studies

Life as You Known?

AI brings risks and you should know of it

DRAG TO EXPLORE

DRAG TO EXPLORE

"Our Future is at Threat"

ChatGPT 5 is safe today but our audit reveals critical vulnerabilities that could threaten the future if ignored. OpenAI's Preparedness Framework shows they are aware of potential risks, yet uncertainty remains about long-term behavior and misuse

"Our Future is at Threat"

ChatGPT 5 is safe today but our audit reveals critical vulnerabilities that could threaten the future if ignored. OpenAI's Preparedness Framework shows they are aware of potential risks, yet uncertainty remains about long-term behavior and misuse

Benefits

The Safety Standard The World Will Run On

Discover how AI audit + CRB Certification enhances efficiency, reduces costs, and drives business growth with smarter, faster processes.

Verified Model Reliability

We evaluate how AI systems behave under pressure, edge cases, and ambiguity to ensure stable, consistent performance that businesses and users can depend on

Verified Model Reliability

We evaluate how AI systems behave under pressure, edge cases, and ambiguity to ensure stable, consistent performance that businesses and users can depend on

Verified Model Reliability

We evaluate how AI systems behave under pressure, edge cases, and ambiguity to ensure stable, consistent performance that businesses and users can depend on

Increased User Trust

When users see that a system passed a CRB audit, they know the model was reviewed for safety, clarity, and fairness. Trust becomes measurable - not assumed

Increased User Trust

When users see that a system passed a CRB audit, they know the model was reviewed for safety, clarity, and fairness. Trust becomes measurable - not assumed

Increased User Trust

When users see that a system passed a CRB audit, they know the model was reviewed for safety, clarity, and fairness. Trust becomes measurable - not assumed

Continuous Oversight

AI systems evolve. We provide ongoing reevaluation to ensure models remain aligned, safe, and predictable over time, not just at launch.

Continuous Oversight

AI systems evolve. We provide ongoing reevaluation to ensure models remain aligned, safe, and predictable over time, not just at launch.

Continuous Oversight

AI systems evolve. We provide ongoing reevaluation to ensure models remain aligned, safe, and predictable over time, not just at launch.

Risk Shielding

Poorly governed AI can result in lawsuits, PR crises, or regulatory penalties. CRB audits identify vulnerabilities before they escalate into financial or public trust damage.

Risk Shielding

Poorly governed AI can result in lawsuits, PR crises, or regulatory penalties. CRB audits identify vulnerabilities before they escalate into financial or public trust damage.

Risk Shielding

Poorly governed AI can result in lawsuits, PR crises, or regulatory penalties. CRB audits identify vulnerabilities before they escalate into financial or public trust damage.

Data-Driven Insights

We analyze how and why the system makes decisions. This transparency helps companies explain outputs to users, regulators, and stakeholders clearly and confidently.

Data-Driven Insights

We analyze how and why the system makes decisions. This transparency helps companies explain outputs to users, regulators, and stakeholders clearly and confidently.

Data-Driven Insights

We analyze how and why the system makes decisions. This transparency helps companies explain outputs to users, regulators, and stakeholders clearly and confidently.

Safe Scaling

We guide companies in scaling AI responsibly, ensuring systems remain safe and effective as adoption expands.

Safe Scaling

We guide companies in scaling AI responsibly, ensuring systems remain safe and effective as adoption expands.

Safe Scaling

We guide companies in scaling AI responsibly, ensuring systems remain safe and effective as adoption expands.

Pricing

The Best AI Certification, at the Right Price

Choose a plan that fits your business needs and let users be confident with AI

Renewal

Initial

Startup

$6,000/Initial

Perfect for small teams starting with AI certification. Begin your journey toward trusted AI systems.

Contact Us

Contact Us

What's Included:

CRB HF-1 Certification

Consumer Risk Alert

1 Major Update Audit

Email & chat support

Up to 1 AI integrations

Pro+

Popular

$15,000/Initial

For growing companies managing multiple AI systems. Expand coverage and strengthen human-trust credibility.

Contact Us

Contact Us

What's Included:

Everything in Startup +

2 Major Update Audit

Consumer Support Team

Priority customer support

Up to 3 AI integrations

Enterprise

Custom

For large-scale AI deployments. Maximum oversight, full credibility, and dedicated guidance.

Schedule a call

Schedule a call

What's Included:

Everything in Pro+

Dedicated Account Manager

Press Release

24/7 Support

Unlimited AI integrations

Renewal

Initial

Startup

$6,000/Initial

Perfect for small teams starting with AI certification. Begin your journey toward trusted AI systems.

Contact Us

Contact Us

What's Included:

CRB HF-1 Certification

Consumer Risk Alert

1 Major Update Audit

Email & chat support

Up to 1 AI integrations

Pro+

Popular

$15,000/Initial

For growing companies managing multiple AI systems. Expand coverage and strengthen human-trust credibility.

Contact Us

Contact Us

What's Included:

Everything in Startup +

2 Major Update Audit

Consumer Support Team

Priority customer support

Up to 3 AI integrations

Enterprise

Custom

For large-scale AI deployments. Maximum oversight, full credibility, and dedicated guidance.

Schedule a call

Schedule a call

What's Included:

Everything in Pro+

Dedicated Account Manager

Press Release

24/7 Support

Unlimited AI integrations

Renewal

Initial

Startup

$6,000/Initial

Perfect for small teams starting with AI certification. Begin your journey toward trusted AI systems.

Contact Us

Contact Us

What's Included:

CRB HF-1 Certification

Consumer Risk Alert

1 Major Update Audit

Email & chat support

Up to 1 AI integrations

Pro+

Popular

$15,000/Initial

For growing companies managing multiple AI systems. Expand coverage and strengthen human-trust credibility.

Contact Us

Contact Us

What's Included:

Everything in Startup +

2 Major Update Audit

Consumer Support Team

Priority customer support

Up to 3 AI integrations

Enterprise

Custom

For large-scale AI deployments. Maximum oversight, full credibility, and dedicated guidance.

Schedule a call

Schedule a call

What's Included:

Everything in Pro+

Dedicated Account Manager

Press Release

24/7 Support

Unlimited AI integrations

FAQs

We’ve Got the Answers You’re Looking For

Quick answers to your questions.

What does CRB | Compliance & Regulation Bureau do

Do you use automated tools or is this done by experts?

We’re a startup. Do we actually need this yet?

What industries need this?

How long does an audit take?

What does CRB | Compliance & Regulation Bureau do

Do you use automated tools or is this done by experts?

We’re a startup. Do we actually need this yet?

What industries need this?

How long does an audit take?

Safety won't derail your progress as much as a simple error can

Book a Call Today and Start Putting Safety First

Book a free call

Book a free call