You should not have to trust us.
How Scribeable actually works — architecture, BAAs, models, prompt structure, pricing logic, data retention, and the things Scribeable does not do well yet. Every claim on this page carries a date. Every claim is verifiable.
As of 2026-04-17. Reviewed quarterly.
Our Architecture
Your audio and PHI travel a specific path. Here is every step.
Audio capture (iOS / web / Apple Watch)
Recording happens on your device. Raw audio is encrypted before it leaves the device. Nothing reaches our servers in plaintext.
Encrypted upload
Audio and any PHI fields travel over envelope-encrypted channels (AES-256-GCM, ECDH P-256 key exchange). The CDN, edge, and reverse proxies never see plaintext.
Transcription
Deepgram nova-3-medical (BAA covered) performs transcription on encrypted audio streams. Transcripts are encrypted at rest immediately after generation.
Two-stage LLM note generation
Anthropic Claude (BAA covered) runs a two-pass pipeline: Stage 1 drafts the note; Stage 2 validates calculators, checks clinical reasoning, and anchors billing codes to specific sentences in the draft.
Storage (Firestore + Firebase + KMS)
PHI is stored field-level-encrypted on Google Cloud (HIPAA-eligible, BAA executed). Each organization has its own data encryption key (DEK), wrapped by a master key encryption key (KEK) managed in Google Cloud KMS.
Retrieval & EHR insertion
Notes are decrypted only at the moment of retrieval, using keys negotiated via ECDH. Browser-extension insertion into the EHR happens on the clinician device; Scribeable servers do not touch the EHR directly.
For the full encryption architecture — see the Security page — including the 5-layer envelope encryption model, ECDH P-256 key exchange, and enforcement-mode details.
For live uptime, latency, and incident history — see the Status page. Updated continuously.
Our BAAs
Every vendor that touches PHI has an executed Business Associate Agreement. Named counterparties — not a vague "we have BAAs in place."
| Counterparty | Scope | Status |
|---|---|---|
| Anthropic | LLM inference for all note-generation and review stages (Claude Opus 4.7, Sonnet 4.6, Haiku 4.5). | Active |
| Google Cloud (Firebase / Firestore / Cloud KMS) | PHI storage, field-level encryption key management, authentication. | Active |
| Deepgram | Medical transcription (nova-3-medical model). Encrypted audio streaming. | Active |
| OVH Public Cloud (HIPAA) | Application server hosting for HIPAA-scoped infrastructure. | Active |
BAAs are executed directly between Scribeable LLC and each named vendor. Copies are available under NDA for covered-entity diligence — contact [email protected].
Our LLM Choices
Which models we use, for what, and what they may and may not do with your data.
Claude Opus 4.7
AnthropicComplex reasoning passes, specialty-specific note refinement, Rounding Mode patient segmentation.
Claude Sonnet 4.6
AnthropicDefault note generation for standard encounters. Quality-pass validation. Billing code anchoring.
Claude Haiku 4.5
AnthropicLightweight summarization, quality-gap nudges, fast UI helpers.
Deepgram nova-3-medical
DeepgramMedical speech-to-text with clinical vocabulary and speaker diarization.
Our Prompt Architecture
How prompts are composed. Structure is public. Verbatim content is not — partial disclosure is a deliberate tradeoff between transparency and clinical risk.
Per-specialty prompt composition
Prompts are composed per encounter from (a) a specialty-specific clinical scaffold, (b) a care-setting layer (outpatient/inpatient/ED), (c) a note-type layer (H&P, progress, ED, SOAP, etc.), and (d) the organization's quality configuration.
Two-pass verification
Stage 1 generates. Stage 2 validates — calculators scored, HCC/MIPS codes anchored to specific draft sentences, quality-gap opportunities surfaced. Stage 2 outputs corrections that the Stage 1 model cannot overrule.
Chart-aware context
Prior encounters, medications, allergies, recent labs, and open quality gaps are injected as context. Context carries across encounters for the same patient.
What we do not publish
Specific prompt text is not published. Publishing verbatim prompts creates clinical risk (competitors produce lookalikes without clinical review) and no educational value. Structure is public; content is protected.
Our Benchmarks
Honest about where we are. Published benchmarks will appear at scribeable.ai/research with full methodology.
Calculator validation accuracy
Methodology: inputs extracted by AI vs. inputs verified by attending; scored against reference implementation. Full methodology and dataset will publish with the study.
Note-quality blinded review
Blinded attending review: AI-drafted vs. attending-written notes, from early users who consented to participate. Results will be published on scribeable.ai/research with full methodology when complete.
Hallucination rate
We have not yet published a hallucination benchmark. We will when the methodology is reproducible — "trust me" metrics get challenged and should.
Our Pricing Logic
Every tier, to the dollar. Every cost driver, named.
Free Trial
14 daysUnlimited notes with Pro features. No credit card required. After trial, account drops to 5 notes/month on the permanent free tier.
Lite
/mo (or $390/yr — 17% off)40 AI notes/month. All note formats. HIPAA + BAA included. Browser extension for any EHR.
Pro
/mo (or $790/yr — 17% off)150 AI notes/month. After-visit summaries. 35+ document types. ICD-10 & HCC coding. Template marketplace. 2 rounding sessions/week.
Team
/seat/mo (or $890/seat/yr)100 notes/seat. All Pro features. Quality reporting dashboard. Population-health insights. 2–10 seats.
Enterprise
Unlimited notes, dedicated support, custom EHR integration, SSO. Priced per engagement — published starting point is available under NDA.
Where the money goes
LLM inference
Two-pass generation runs primarily on Claude Sonnet 4.6 with Opus 4.7 for reasoning-heavy passes. Cost per note scales with encounter length, specialty complexity, and how many chart-context passes run.
Transcription
Deepgram nova-3-medical charges per minute of audio. Rounding Mode amortizes this across many patients.
Storage + compute
Firestore, Cloud Functions, KMS, and HIPAA-scoped hosting on OVH. Costs grow linearly with stored encounters and user count.
Support
Support is answered by the founder directly through 2026. Scales to a support team as usage grows.
Gross margin: We will publish a gross-margin range in the first quarterly transparency report (Q4 2026). We are not yet publishing a number because we want it to be one we can stand behind with audited math — not an estimate. The honest answer today is that per-note margin is positive across all tiers; precise tier-level numbers will appear in the quarterly report.
Our Data Retention
What we keep, for how long, how you export, how you delete.
Encounter recordings
Stored encrypted for the life of the account. User can delete any single recording at any time from the app; deletion is permanent within 30 days.
Generated notes
Stored encrypted for the life of the account. Exportable at any time in structured JSON or plain text.
Transcripts
Stored encrypted, linked to the associated encounter. Deletable with the encounter.
Account deletion
On account closure, all PHI is permanently deleted within 30 days. Audit-log records of access (which do not contain PHI) are retained per HIPAA minimum-retention requirements.
Export
Full account export (all notes, templates, documents) is available from the web dashboard at any time. Export is available even during cancellation.
Our Limitations
Honesty beats overselling. Things Scribeable does not do well yet.
Our Incident History
Security incidents, outages, and accuracy regressions will be logged here as they occur — not retroactively summarized.
No reportable HIPAA breaches
We have not had a HIPAA-reportable breach. We commit to publishing incident summaries on this page when and if they occur, within the HIPAA-mandated notification timeline.
Quarterly transparency report
Starting Q4 2026 we publish an 8–10 page quarterly PDF: uptime, latency, accuracy benchmark updates, incidents, customer-count (anonymized), support response metrics, feature shipping cadence.
Found something wrong? Tell us.
A page like this only works if it is accurate. If you spot a factual error, an out-of-date claim, or a gap, email [email protected]. We will correct within five business days and log the correction in the next quarterly transparency report.
Last reviewed: 2026-04-17 · Next scheduled review: quarterly
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