AI Governance for AI Teams —
Build Safely While Moving Fast
Your AI team moves fast. Regulators and enterprise clients are moving fast too. QuickHire AI governance engineers embed in your team — running bias audits, building compliance docs, and testing adversarial robustness — without slowing your deployment cadence.
4hr/$100 · 8hr/$200 · Sprint Pack 10 days/$1,700 · No lock-in
The Governance Gap Most AI Teams Have
Building AI products without governance isn't faster — it's a debt that comes due at the worst time.
Regulation Without Readiness
EU AI Act enforcement begins August 2026. High-risk AI systems must have conformity assessments, bias audits, and human oversight mechanisms — most teams haven't started.
Enterprise Procurement Blockers
Enterprise clients now require AI governance documentation before signing contracts. No model cards, no bias reports, no audit trail → no deal. Governance becomes a revenue problem.
Hidden Model Risks
Prompt injection, adversarial inputs, training data bias, hallucination rates — these aren't theoretical. Real AI products in production have been exploited, discriminatory, or quietly wrong at scale.
AI Governance Work We Do for AI Teams
Embedded governance alongside your ML engineers — not a separate audit that blocks your roadmap.
EU AI Act Compliance
System classification (minimal/limited/high-risk/GPAI), conformity assessment, CE marking prep, transparency reports, and ongoing compliance monitoring for your AI product.
AI Risk Assessment
NIST AI RMF-aligned risk mapping — identify, measure, manage, and govern AI risks across your models. Deliverable: prioritized risk register with mitigation plans.
Bias & Fairness Testing
Disparate impact analysis, protected attribute testing, counterfactual fairness evaluation — across model predictions, RAG outputs, and LLM responses. Includes bias mitigation strategies.
Model Documentation
Model cards, data sheets, training data provenance, performance benchmarks across subgroups, known limitations — the documentation enterprise clients and regulators require.
Adversarial AI Security
Prompt injection testing, jailbreak resistance, adversarial input generation, model extraction defense, and output filtering — for LLMs, RAG systems, and ML classification models.
Human Oversight Systems
Human-in-the-loop workflow design, escalation pathways, model override mechanisms, and audit trails for high-stakes AI decisions — required by EU AI Act for high-risk systems.
Regulatory Frameworks We Cover
How QuickHire Embeds AI Governance in Your Team
Governance Gap Assessment
PM + AI governance engineer map your current AI systems against applicable regulations. Output: risk classification, compliance gaps, priority actions, and timeline. Deliverable in session 1.
Parallel Track Work
Governance engineer works alongside your ML engineers — reviewing model updates, running bias tests on new versions, documenting training data decisions, and flagging risks in real time.
Compliance Documentation
Model cards, risk registers, data lineage documentation, conformity assessment artifacts — built as your product evolves, not as a retrospective audit that slows everything down.
Security & Adversarial Testing
Red-teaming your LLM and ML models — prompt injection, jailbreaks, adversarial inputs, membership inference — with a written report and recommended mitigations before each major release.
AI Teams Who Need This Now
Enterprise AI Platform Teams
You're building internal AI tools that employees or customers use. Legal is asking hard questions about bias and explainability. You need a governance engineer before your next board review.
LLM Product Startups
You've shipped a ChatGPT-powered product and your first enterprise client is asking for a model card and bias report. You need governance documentation in 2 weeks — not 6 months.
Healthcare / FinTech AI Teams
You're building AI in a regulated sector. FDA AI/ML guidance, FCA AI rules, or EU AI Act high-risk classification applies. You need an expert who knows both AI and the specific regulatory context.
Tools & Frameworks We Use
Pricing
Simple, Transparent Pricing
Every session includes a vetted expert + dedicated PM. Cancel anytime.
India · INR
GST Invoice · GST included
Starter
Best for first timers & quick tasks
/ session
GST included
- 1 vetted expert
- Dedicated PM included
- Cancel after session
- Tax-compliant invoice
Full Day
Most chosen for serious delivery
/ session
GST included
- 1 vetted expert
- Dedicated PM included
- Daily progress report
- Priority assignment
- Tax-compliant invoice
Available in 14 countries · Other currencies available at checkout
FAQ
Frequently Asked Questions
AI governance is the set of policies, processes, and controls that ensure AI systems are safe, fair, transparent, and compliant. Your AI team needs it because: regulators are moving fast (EU AI Act, US Executive Order on AI), enterprise clients require it for procurement, and ungoverned AI systems create legal and reputational risk. A governance engineer works alongside your ML engineers to build audit trails, bias tests, and compliance documentation without slowing down development.
It depends on your deployment region and use case. EU AI Act (applies to any AI system used in the EU — enforcement starts August 2026 for high-risk systems). US NIST AI RMF (voluntary framework but expected by US federal clients). UK AI Safety Institute guidance. Financial sector: FCA / SEC AI rules. Healthcare: FDA AI/ML guidance. Our AI governance engineers assess your specific system against the relevant frameworks and prioritize what to implement first.
A lightweight AI risk assessment (classify your system, identify top risks) takes 1–2 sessions (4–8 hours). A full compliance audit for EU AI Act high-risk classification takes 2–4 weeks. Building a governance framework from scratch (policies, model cards, audit trails, monitoring) takes 4–8 weeks. Your PM scopes the engagement precisely based on your current state and compliance deadline.
Yes — this is the primary engagement model. Your ML engineers keep building; the governance engineer runs parallel tracks: bias testing on new model versions, documentation of training data provenance, adversarial robustness testing, and building the compliance dossier. No slowdown to your core product work.
The EU AI Act classifies AI systems by risk. General-purpose AI models (GPT-4, Claude, Llama) used in products are subject to transparency requirements (model cards, capability disclosures). High-risk systems (AI in hiring, credit scoring, healthcare, law enforcement) face strict conformity assessment, bias auditing, human oversight, and documentation requirements. "Unacceptable risk" systems (mass surveillance, social scoring) are banned. Our engineers help you classify your system and build the required compliance artifacts.
Yes. Prompt injection (where user input manipulates your system prompt to override intended behavior), adversarial inputs (crafted inputs that cause incorrect outputs), model extraction attacks (reverse-engineering your model via API), and data poisoning (malicious training data influencing model behavior) are all covered by our AI security engineers. These are distinct from traditional application security and require AI-specific expertise.
More Resources for AI Teams
Build AI Responsibly — Without Slowing Down
AI governance engineer + PM assigned in 10 minutes. Start with a gap assessment and leave with a compliance roadmap.
Book an AI Governance Engineer →4hr/$100 · Sprint Pack 10 days/$1,700 · Cancel anytime