Relm Pro is an AI-powered product, which makes how we use AI a question worth a clear answer. This page is that answer.
TL;DR
- We use multiple frontier model providers for different tasks.
- Your data is not used to train any provider's models. This is contractual via their enterprise APIs and is verified by our DPA.
- We don't train or fine-tune AI models on your uploaded documents or property financials without your explicit consent.
- We don't share your data with any other third party for AI purposes.
Which providers we use
We route different tasks to different models based on what each is best at:
- Reasoning-heavy steps (the AI Summary, the pro-forma generation chain) — frontier reasoning models.
- Structured extraction (rent-roll parsing, P&L line-item recognition) — frontier general-purpose models.
- Embeddings (turning document chunks into vectors for chat retrieval) — production embedding models.
- Vision and OCR — a mix of frontier vision models and traditional OCR engines.
The mix evolves as model quality and pricing change. The important constant is the data-handling posture.
On Enterprise plans you can choose which provider — Google Gemini, Anthropic Claude, or OpenAI GPT — powers your Intel Report runs, in Settings → AI provider.
What we send
- Property data and uploaded documents are sent to model providers as needed to answer chat queries, generate summaries, or build pro-formas.
- Documents are sent as uploaded. We don't automatically remove personal details such as tenant names, so redact anything you don't want processed before you upload it.
- Internal Relm logs are not sent to model providers.
What we don't do
- No training. No provider trains models on your data, period. This is enforced via the providers' enterprise / API tier — we use those tiers explicitly for this reason.
- No cross-customer data sharing. Your data is scoped to your organization. The model never sees data from another customer alongside yours.
- No retention beyond inference. Provider APIs don't retain your data beyond the immediate inference call (subject to short-window logging for abuse-prevention, also covered in their DPAs).
Our own model fine-tuning
We don't use your uploaded documents or property-specific financial data to train or fine-tune AI models — ours or any provider's — without your explicit consent.
We do build and tune our own prompts, retrieval pipelines, and evaluation suites. Our privacy policy allows aggregated, de-identified usage and chat-interaction data — data that can't identify you — to be used to train, evaluate, and improve our own models and research agents.
What's logged inside Relm
We log enough to operate the service: API request metadata, error rates, agent latencies. Traces of AI requests — which can include the text sent to and returned by the model — are recorded for debugging and usage accounting, and expire automatically.
When you have specific compliance needs
Enterprise customers with strict compliance regimes (DPA addendums, BAAs, custom data-residency) can talk to our team. We support most institutional requirements.