Honest 10-way comparison of AI Infrastructure — Privacy, Data Residency & Self-Host Comparison (Zero-Data-Retention Contracts · BAA Availability · Data Residency · Self-Host Options) across Anthropic · OpenAI · Google Vertex AI · AWS Bedrock · Together AI · Replicate · OpenRouter · Modal · Fireworks AI · Groq platforms. No vendor sponsorship. Calling Matrix by buyer persona below — operator's siren-based read on which one to pick when you're forced to pick.
Honest read on positioning, ideal customer, and where each one is the wrong call. No vendor sponsorship, no affiliate links — operator-grade signal.
The strongest enterprise privacy posture among frontier AI vendors — zero-data-retention contracts on Enterprise tier, HIPAA BAA available, SOC 2 Type II, ISO 27001. Default API does not train on customer data (per current Anthropic ToS). Enterprise tier extends to ZDR (no retention beyond request lifetime) + custom data-residency contracts. Anthropic Claude is also available inside AWS Bedrock (AWS BAA + GovCloud) and Google Vertex AI (GCP IAM + audit) for buyers who need procurement inside a major cloud compliance umbrella.
API does not train on customer data by default (per current OpenAI ToS) — Enterprise tier extends to ZDR contracts. HIPAA BAA available via Azure OpenAI (Microsoft compliance umbrella) — direct OpenAI API doesn't currently offer BAA. SOC 2 Type II in hand. The Microsoft / Azure OpenAI variant gives buyers OpenAI models inside Microsoft's full compliance umbrella (FedRAMP via Azure GovCloud for some workloads, BAA via Azure, etc).
GCP-native privacy posture — BAA via Google Cloud, multi-region data residency on GCP infrastructure, GCP IAM + audit + KMS encryption integration. Vertex Model Garden offers some open-source models you can deploy in your own GCP project (closer to self-host than direct API). Anthropic Claude on Vertex inherits GCP procurement + IAM + audit posture. The right pick when you want Anthropic Claude or Gemini inside a single GCP compliance boundary.
The AWS-native procurement-defensible default for AI infrastructure privacy — BAA via AWS, GovCloud variant for FedRAMP High workloads, CloudTrail audit, KMS encryption, VPC endpoint isolation. Anthropic Claude on Bedrock is contractually inside AWS BAA + GovCloud — most regulated AWS shops route Claude through Bedrock specifically for this. Provisioned Throughput offers dedicated capacity inside your AWS account. Multi-model marketplace (Anthropic + Llama + Mistral + Cohere + Amazon + Stability) all served from one AWS API.
SOC 2 Type II + dedicated endpoints + the path to self-host (Llama / DeepSeek / Qwen weights are open). Together hosts open-source models, so the underlying weights are downloadable — if Together's privacy posture isn't enough, you can self-host the same model on your own GPUs. Dedicated endpoints offer single-tenant inference. The right OSS-first privacy story if you want a path to full self-host without changing model.
SOC 2 Type II + cloud-only by design — your code, model, and inference run inside Replicate's environment. Privacy posture is fine for prototyping, evaluation, and non-regulated workloads. For regulated production, you'd typically deploy the same open-source model on Modal (your AWS / GCP / Azure account) or self-host on your own GPUs. Replicate's value is prototyping velocity, not enterprise privacy depth.
Privacy posture inherits the upstream provider you route to — transparent about which provider serves which request. If you route to Anthropic via OpenRouter, the request inherits Anthropic's ZDR + privacy posture. If you route to OpenAI, you inherit OpenAI's ToS. OpenRouter itself has SOC 2 Type II and does not train on customer data. The trade-off: you can't get the same enterprise contracts (BAA, custom DPA, custom rate limits) through OpenRouter that you'd get going direct.
SOC 2 Type II + the option to deploy Modal infrastructure inside your own AWS / GCP / Azure account (Enterprise tier). The right pick when you want serverless GPU compute with enterprise privacy posture — Modal manages the platform, your code + data + models run inside your cloud account perimeter. Closer to self-host than any other vendor on this list except direct self-host.
SOC 2 Type II + HIPAA BAA available on enterprise tier + dedicated deployments (single-tenant inference). Strongest privacy posture among the OSS-hosting specialists — HIPAA BAA puts Fireworks ahead of Together for healthcare-adjacent OSS workloads. Open-weight models mean you have a path to self-host if Fireworks' posture isn't enough. Dedicated deployments offer single-tenant inference inside Fireworks-managed infrastructure.
SOC 2 Type II + enterprise privacy posture emerging — GroqCloud Enterprise offers private deployments of LPU infrastructure for regulated customers. The privacy story is younger than frontier vendors but improving fast. Open-weight models served on LPU mean you have a path to self-host the same model on GPU if needed (with the latency trade-off). The right pick when sub-100ms latency is the deciding factor and SOC 2 is enough for your workload.
Most comparison sites refuse to forced-rank because their revenue depends on staying neutral. SideGuy ranks because it doesn't take vendor money. Here's the call by buyer persona.
Your problem: You're building OSS, side projects, or non-regulated workloads. Privacy isn't your bottleneck — velocity + cost are. You want the best AI substrate without worrying about BAA / DPA / ZDR contracts.
Your problem: Your IP matters but you're not regulated (no PHI / PCI / FedRAMP / GDPR-strict). You want enterprise-tier privacy controls (your data doesn't train future models, ZDR contracts available) without full self-host.
Your problem: Your workload touches PHI / PCI / PII. Sending it to an AI API risks compliance violation. You need vendor with enterprise BAA + SOC 2 + maybe self-host. Cross-link to HIPAA ePHI Continuous Monitoring axis for the broader vendor stack.
Your problem: You're DoD-adjacent or intelligence. Cloud-only AI is a non-starter or limited to GovCloud. You need FedRAMP authorization and ideally a path to on-prem self-host. Limited vendor options.
These rankings are SideGuy's lived-data + observed-buyer-pattern read as of 2026-05-11. They're directional, not gospel. The right answer for YOUR specific situation may diverge — text PJ for a 10-min operator-honest read on your actual buying context.
Vendor pricing + features + market positioning shift quarterly. SideGuy may earn referral commissions from some of these vendors, but rankings are independent — affiliate relationships never change rank order. Sister doctrines: /open/ live operator dashboard · install packs · operator network.
Or skip all of them. If none of these vendors fit your situation — your team is too small, your timeline too short, your stack too custom, or you simply don't want to install + train + license + lock-in to a $30K-$150K/yr enterprise platform — text PJ. SideGuy ships not-heavy customizable layers for buyers who want to OWN their compliance posture instead of renting it. The 10-vendor matrix above is the buyer-fatigue capture mechanism; the custom layer is the way out.
Depends on the vendor and the tier. Anthropic API does NOT train on customer data by default (per current Anthropic ToS) — Enterprise tier extends to ZDR contracts. OpenAI API does NOT train on customer data by default (per current OpenAI ToS) — Enterprise tier extends to ZDR. AWS Bedrock contracts inherit AWS's no-training-on-customer-data posture across all hosted models. Google Vertex AI inherits GCP's no-training-on-customer-data posture. Together AI / Fireworks AI / Replicate / OpenRouter / Modal / Groq all explicitly state no training on customer data on standard tiers (verify each vendor's current ToS — these terms have changed multiple times and will keep changing). Always re-check current ToS at the time you contract.
'No training' means your data is NOT used to train future models — but the vendor may still log requests for abuse monitoring, debug, or 30-day retention windows. 'Zero data retention' (ZDR) means your data is NOT retained beyond the request lifetime — once the response is returned, the prompt + response are dropped. ZDR is typically Enterprise-tier-only and is required for HIPAA BAA / PCI scope / GDPR-strict workloads. Anthropic + OpenAI + AWS Bedrock + Google Vertex AI all offer ZDR contracts at Enterprise tier. The difference matters: 'no training' is the default; 'ZDR' is the procurement-defensible posture for regulated workloads.
FedRAMP-authorized AI infrastructure is concentrated in the cloud-native variants: AWS Bedrock via AWS GovCloud (FedRAMP High for many workloads), Azure OpenAI via Azure GovCloud (FedRAMP for many workloads), Google Vertex AI via Google Cloud GovCloud variants (verify scope per workload). Direct API vendors (Anthropic, OpenAI direct) do not currently have FedRAMP — most fed-adjacent customers route through the cloud-native variants. Always confirm scope with your contracting officer — 'available on GovCloud' is not the same as 'FedRAMP authorized for this specific use.' For pure air-gapped workloads, the only realistic path is self-host (Llama / DeepSeek / Qwen on your own GPUs in your fed-authorized environment).
Yes — three realistic paths in 2026: (1) Self-host open-weight models (Llama 3.x / DeepSeek-V3 / Qwen 2.5) on your own GPUs in your air-gapped environment — the OSS weights are downloadable, the velocity trade-off vs frontier-cloud (Claude / GPT-5) is real but narrowing; (2) AWS Bedrock GovCloud + Anthropic Claude inside the FedRAMP High boundary — closest to air-gapped while still using a commercial frontier model; (3) Modal Enterprise tier deployed inside your air-gapped cloud account with self-hosted open-weight models — serverless GPU with enterprise privacy posture inside your perimeter. The fed-adjacent default in 2026 is AWS Bedrock GovCloud for commercial frontier model access; pure air-gapped DoD work still uses self-hosted OSS.
Two reasons. (1) Anthropic ships ZDR contracts + HIPAA BAA + SOC 2 Type II + ISO 27001 transparently, with a published Trust Center and direct ToS that operators can read without negotiation. (2) Claude's model behavior — refuses to fabricate when uncertain — is itself a privacy-relevant property: a model that confidently fabricates user data, account context, or PII based on partial input is a privacy risk regardless of contractual posture. Operator-honest model behavior + transparent enterprise contracts together = the production-trust posture SideGuy bets on. PJ uses Anthropic API daily to ship the entire SideGuy site (compliance graph + dashboard + Calling Matrix pages). Eat-your-own-dogfood at the trillion-dollar substrate level. See AI Coding Tools comparison for the IDE-substrate operator-honest decision.
The AI Infrastructure cluster covers six operator-honest pages: 10-Way Megapage (Anthropic · OpenAI · Vertex · Bedrock · Together · Replicate · OpenRouter · Modal · Fireworks · Groq) · Operator-Honest Ratings axis (Quality of Support · Uptime · Roadmap Velocity · Operator-Honest Behavior) · Pricing & TCO axis (per-token vs flat vs serverless GPU vs self-host) · Inference Speed + Latency axis (sub-100ms · tokens-per-second · batched) · Multi-Provider Routing + Vendor Lock-In axis (OpenRouter · Bedrock multi-model · Vertex multi-model). Plus the sister cluster: AI Coding Tools 10-Way Megapage. And the broader graphs: Compliance Authority Graph · Operator Cockpit · Install Packs. Same operator-honest doctrine across every page: no vendor sponsorship, siren-based ranking by buyer persona, parallel-solutions custom-layer pitch (buy from whatever vendor you want — but you're going to want a SideGuy).
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