Choosing an LLM vendor under regulated constraints.
BAA availability, retention defaults, region options, and eval portability — how Brandlabs shortlists model providers for healthcare and regulated buyers.
·8 min read
TL;DR
Pick LLM vendors on contract posture and control surfaces first, model leaderboard second. For regulated AI, Brandlabs scores BAA/DPA readiness, retention and training defaults, regional processing, logging, and how hard it is to swap providers when evals say the model drifted.
What should beat “which model is smartest” in a vendor shortlist?
Whether you can put PHI or personal data on the path at all: BAA or equivalent, zero-retention options, training-on-inputs off by default, regional endpoints, and audit-friendly logging. A brilliant model you cannot contract for is a demo, not a vendor.
Scorecard columns we use in Discovery Sprints:
- Contract: BAA / DPA availability and subprocessors
- Data: retention, training, abuse review access to prompts
- Region: US / EU / IN processing options
- Control: key management, VPC / private networking if needed
- Operability: rate limits, status page, version pinning
- Portability: can our eval suite run against an alternate model?
Leaderboards inform the bake-off. They do not clear compliance.
How do you keep from locking into one model API?
Abstract prompts behind templates, keep fixtures model-agnostic, and require a second-provider smoke path in CI. When a vendor changes retention or pricing, you need a measured migration — not a rewrite.
Portability habits:
- Prompt templates versioned in repo
- Tool schemas independent of vendor SDK quirks
- Eval gates that can target provider A or B
- Documented “break glass” alternate model for outages
Regulated buyers care that you can survive a vendor event without losing the audit story.
When is on-prem or private inference worth it?
When contracts, residency, or customer policy forbid the cloud path you wanted — or when latency/cost at volume favors it. Fear alone is a weak reason; an explicit threat model and total cost of ownership are strong ones.
We decide with a matrix: data sensitivity, customer demands, talent to operate GPUs, and whether a private endpoint from a major vendor already satisfies the constraint.
Most early-stage products overbuy isolation and underbuy evals.
Frequently asked questions
Do we need a BAA with every model provider?
If they can create, receive, maintain, or transmit PHI for you, treat them as a business associate until counsel says otherwise. Synthetic-only prototypes can wait.
Is this legal advice?
No. Vendor contracting is a counsel decision. We implement the technical posture those contracts require.