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For CTOs & Engineering Leaders

Your teams are using 8+ AI tools across 15+ different teams. You have zero visibility into what they’re using, what policies they’re following, and whether they’re leaking data. Meanwhile, your CEO is asking about AI governance maturity, and your board wants compliance proof. This quickstart gets you unified governance in 30 minutes.

The TruthVouch Difference

Traditional approach: Manual policy creation, manual enforcement (ask teams to follow rules), no visibility until an incident, reactive security posture.

With TruthVouch: Auto-discovery of all AI tools, auto-enforcement via network policy engine, continuous monitoring with alerts, AI-powered fact-checking on every LLM response. From zero to full governance in 30 minutes.

Step 1: Assess Your AI Maturity (5 minutes)

Before you build governance, understand where you stand — and get a data-driven roadmap for what to build next.

  1. Go to TruthVouch AI Advisor Assessment (or start from the dashboard after signup)
  2. Answer 25 quick questions about your current AI usage, tools, governance practices, and technical controls (5 minutes)
  3. You’ll get:
    • A maturity score (0-100) across 6 dimensions: Strategy, Governance, Technical, Ethical, Operational, Data
    • Benchmark against your industry (how you compare to peers)
    • Specific gaps ranked by impact
    • Tool recommendations (Shield, Governance, Compliance, etc.)
    • Implementation roadmap with priorities

Save this report. You’ll use it to brief your executive team on why governance infrastructure is essential, and to track progress quarter-over-quarter.

Step 2: Define Your Truth (15 minutes)

All TruthVouch products depend on Truth Nuggets — verified facts about your organization. Your engineers need these to:

  • Detect hallucinations in public AI engines
  • Fact-check internal LLM calls via the Trust API
  • Prove governance in compliance scans
  • Certify AI-generated content

During signup, you’ll see an onboarding wizard that guides you through creating initial Truth Nuggets:

  1. Product information (3 minutes)

    • Product names and descriptions
    • Feature lists
    • Pricing tiers
    • Launch dates

  2. Company information (5 minutes)

    • Leadership (CEO, founders, key execs)
    • Company founding date
    • Headquarters location
    • Funding status and stage

  3. Policies and claims (7 minutes)

    • Data retention policies
    • Security practices (encryption, SOC 2, etc.)
    • Privacy statements
    • Certifications
    • Key capabilities and differentiators

Pro tip: You don’t need to be complete. Start with your top 20-30 facts. You’ll add more over time. Most teams spend 15 minutes creating initial Nuggets and expand later.

Step 3: Deploy Hallucination Monitoring (10 minutes)

Start detecting when public AI engines get facts wrong about your company.

  1. From your dashboard, go to Shield → Cross-Check Schedule
  2. Create cross-check schedules:
    • For critical facts (CEO, funding status, core product features): Every 1 hour
    • For less critical facts (secondary features, partnerships): Every 24 hours
  3. Select which AI engines to monitor:
    • Default: ChatGPT, Gemini, Perplexity, Claude (big 4)
    • Optional add-ons: Bing, DuckDuckGo, Brave, You.com, Phind
  4. Save and activate

Within 24 hours, you’ll see your first cross-check results and Brand Trust Score. You’re now monitoring what every major AI engine is saying about your company — automatically.

Step 4: Deploy the Governance Firewall (5-10 minutes)

Govern internal LLM calls — fact-checking, PII masking, policy enforcement.

Option A: SDK Integration (5 minutes, for application LLM calls)

If your teams are using LLMs in production applications (customer support, research, summarization):

  1. Go to Governance → Trust API → Getting Started
  2. Copy your API key
  3. Install the SDK for your language (Python, TypeScript, C#, Java):
    Terminal window
    # Python example
    pip install truthvouch-trust
  4. Wrap your LLM client in 3 lines: 
    from truthvouch_trust import TruthVouch
    client = TruthVouch(api_key="your-api-key")
    # Now every LLM.completion() call goes through fact-checking
  5. Deploy to staging, verify latency (should be sub-200ms), then prod

Every LLM response is now automatically fact-checked against your Truth Nuggets and flagged alerts if hallucinations are detected. You can handle alerts in code (log, notify, override).

Option B: Sentinel Agent (10 minutes, for employee AI tools)

If employees are using ChatGPT, Copilot, Claude, Cursor on their laptops:

  1. Go to Governance → Sentinel → Download
  2. Download the MSI (Windows) or PKG (macOS) installer
  3. Deploy via:
    • Group Policy (Windows) — GPO push to all domain machines
    • Intune (Windows) — Add to device configuration
    • Jamf (macOS) — Add to managed deployment
    • Manual — Email installer link to team leads
  4. Once deployed, Sentinel intercepts all employee AI tool traffic and auto-enforces your policies

Agents appear in your Governance Dashboard within 5 minutes of first connection.

Step 5: Configure Basic Auto-Enforced Policies (5 minutes)

Define the rules for what’s allowed and what’s blocked. TruthVouch auto-enforces them.

  1. Go to Governance → Policy Engine
  2. Create a basic policy: 
    rule "block_unapproved_tools" {
      if tool not in ["chatgpt", "claude-web"]
        then block()
        else allow()
    }
    

    rule "mask_pii" {
      mask(regex="ssn|credit_card|api_key")
    }
  3. Test the policy (editor has sandbox mode)
  4. Publish to Staging first, then Production

Policies are written in Rego (open-source policy language). If you don’t have a policy expert, we provide 10 pre-built templates (data classification, PII masking, tool blocking, content safety).

Step 6: Monitor the Dashboard (ongoing)

You now have three dashboards to monitor:

  1. Shield Dashboard — Brand Trust Score, hallucinations detected, corrections deployed
  2. Governance Dashboard — Policy enforcement, blocked requests, audit trail, Sentinel agent status
  3. Trust API Dashboard — API usage, fact-check accuracy, latency metrics

Set a daily standup to check:

  • Any Critical alerts from Shield
  • Policy violations in Governance
  • API errors in Trust API

Your team can set up Slack notifications so you don’t have to check manually.

What Happens Next (Month 2-3)

Once Firewall is live and policies are enforced:

  1. Run Compliance Scan (20 minutes)

    • Map your AI systems to EU AI Act, ISO 42001, GDPR, SOC 2
    • Identify gaps
    • Auto-generate remediation tasks

  2. Generate Board Report (5 minutes)

    • Export governance summary
    • Include metrics (hallucinations prevented, policies enforced, audit trail)
    • Show trend over time

  3. Expand to Other Teams

    • Share SDK with other engineering teams
    • Deploy Sentinel to more departments
    • Create team-specific policies

Integration Examples

Python + OpenAI

from truthvouch_trust import TruthVouch
from openai import OpenAI


client = OpenAI()
truth = TruthVouch(api_key="your-api-key")


response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "What is TruthVouch?"}]
)


# Fact-check the response
result = truth.verify(
    text=response.choices[0].message.content,
    context="about_company"
)


if not result.is_accurate:
    print(f"Hallucination detected: {result.alert}")
    # Handle alert in your app logic

Next Steps

  1. Complete onboarding (define Truth Nuggets)
  2. Deploy to one team as pilot (1-2 weeks)
  3. Collect metrics (hallucinations prevented, false positives)
  4. Roll out to all teams
  5. Run compliance scan and generate board report

Questions? Reach out to your solutions engineer or post in the in-app support chat.