Groq AI Vendor Risk Profile
AI inference company building custom Language Processing Units (LPUs) and GroqCloud inference platform delivering ultra-low-latency inference for open-source models (Llama, Mixtral, Gemma). Hybrid model combining proprietary silicon hardware with cloud inference service.
Risk overview
Risk score: 31/100
Risk tier: Moderate
Safety rating: 69/100 (higher is better)
Lower risk scores indicate lower assessed risk.
Last verified: Apr 19, 2026 Aging
Risk dimensions
| Dimension | Risk score |
|---|---|
| Data Handling | 28/100 |
| IP Exposure | 26/100 |
| Jurisdiction | 13/100 |
| Security | 34/100 |
| Regulatory Compliance | 50/100 |
| Transparency | 70/100 |
| Business Stability | 23/100 |
| Dependency Chain | 31/100 |
| Agent Governance | Not assessed |
Analyst summary
Rating: Acceptable
Groq runs inference on its own LPU silicon, offering an ultra-low-latency alternative to Nvidia-dependent stacks with clean no-training defaults and SOC 2 Type II attestation. Enterprise maturity is still catching up to hyperscaler-class compliance, and the company is in a capital-intensive chip-scaling phase.
Bottom line: Acceptable for commercial workloads seeking an Nvidia-alternative inference path; verify compliance fit against your requirements.
Strengths
- Proprietary LPU silicon provides a Nvidia-alternative inference path with class-leading latency
- No training on customer inputs and ephemeral handling by default
- SOC 2 Type II attested, with DPA and EU inference regions for GDPR workloads
- HIPAA BAA available on Enterprise tier
Concerns
- Enterprise compliance footprint narrower than hyperscalers (no FedRAMP, limited ISO coverage disclosed)
- Capital-intensive chip business with sustained heavy spend relative to revenue
- Model menu limited to hosted open-source models (Llama, Mixtral, Qwen); no frontier proprietary model
- Concentrated strategic relationships (Saudi Arabia, Meta) introduce customer-concentration dynamics
Best for
- Latency-sensitive inference workloads (voice agents, real-time assistants)
- Teams wanting Nvidia-independent infrastructure diversification
- Open-source model deployments at scale with strong performance per dollar
Avoid if
- You need a FedRAMP-authorized inference provider today
- Your workload depends on frontier proprietary models (GPT-5, Claude, Gemini) that Groq does not host
- You require deep enterprise tooling parity with Azure OpenAI or Vertex AI
Citations
- Data Handling — Data Retention Period
API inputs and outputs are processed ephemerally and are not retained beyond the duration required to return a response, except for limited operational logs.
- Data Handling — Hipaa Baa Available
HIPAA Business Associate Agreements are available to Groq Enterprise customers upon request.
- Data Handling — Trains On User Data
Groq does not use Customer Input or Output submitted through the GroqCloud API to train, retrain, or fine-tune its underlying models.
- Governance — Financial Stability
Groq's LPU architecture is positioned as an alternative to Nvidia GPUs for inference workloads, with customer commitments from Saudi Arabia's Aramco Digital and Meta partnerships.
- Governance — Strategic Investors
AI chip startup Groq raised $640 million in a Series D round led by BlackRock, valuing the company at $2.8 billion.
- Jurisdiction Profiles — Incorporation Country
Groq, Inc. is a Delaware corporation headquartered in Mountain View, California.
- Security Compliance — Gdpr Compliant
Groq offers a Data Processing Addendum for customers processing EU personal data and operates EU inference regions for data residency.
- Security Compliance — Soc2 Type2
Groq has achieved SOC 2 Type II attestation covering the GroqCloud inference platform.