What a Audio Transcription Service actually does
Transcribes audio or video uploads with speaker diarization, generates structured summaries and action items, and delivers the output through a fully white-labeled dashboard where the bot and brand are yours.
A white-label audio transcription service accepts audio files (MP3, M4A, WAV, WebM) via upload or live meeting bot ingestion (Zoom/Meet/Teams via Recall.ai at ~$0.13/hr), runs them through a speech-to-text model (Deepgram Nova-3 at $0.0043/min batch — 5.26% WER accuracy leader), optionally adds speaker diarization ($0.12/hr add-on), and sends the full transcript to a foundation LLM (Claude Sonnet 4.6 at $3/$15 per M tokens, or GPT-5.4 mini at $0.75/$4.50 for cost-sensitive tiers) to generate a structured summary, action items, decisions, and blockers. All output is stored per-tenant in Supabase with RLS and delivered through a dashboard branded with your logo and domain.
The critical 2026 fact is that there is no honest white-label SaaS in this category. Otter.ai has no white-label tier. Fireflies.ai provides a GraphQL API on Business/Enterprise but no rebrandable dashboard. Sembly offers webhooks only. MeetGeek Business at $17/user/mo brands the summary only — the Zoom/Meet/Teams bot still joins with the visible identity 'MeetGeek Notetaker,' revealing your stack to every meeting participant. This is the decisive argument for a custom build: the meeting-bot identity is the product, and no vendor sells a rebrandable bot.
AI capabilities involved
Speech-to-text with speaker diarization
Real-time streaming transcription
LLM summarization and action-item extraction
Meeting bot ingestion
Multi-language transcription
Who uses this
- Agencies selling branded meeting-intelligence tools to their SMB clients under their own label
- B2B SaaS founders adding meeting notes as a workflow feature for existing customers
- Sales-team-tool builders who want a 'your company's meeting coach' branded bot
- Legal-tech or medical documentation providers who need HIPAA-compliant transcription (Deepgram BAA path)
- Professional-services firms (consulting, law, accounting) offering branded note-taking as a client service
SaaS alternatives on the market
Real products you can sign up for today — with current 2026 pricing, honest pros and cons.
MeetGeek
Agencies whose clients already use MeetGeek and won't notice the bot name — or where summary-only branding is sufficient for the value proposition
Basic free plan (limited summaries)
$17/user/mo (Business, annual billing)
Quote-based
Pros
- +Summary branding is available — you can white-label the email report that gets sent after meetings
- +Supports Zoom, Google Meet, Microsoft Teams, and Webex automatically
- +4.6/5 Capterra rating with real enterprise reviews
- +Calendar sync and automatic meeting detection work reliably
Cons
- −The bot that joins meetings is still called 'MeetGeek Notetaker' — visible to every participant in the calendar invite and meeting lobby
- −Only the summary output is branded, not the platform dashboard
- −Per-user pricing at $17/mo means 200-user agency costs $3,400/mo — payback on a custom build is under 8 months
- −CRM integrations and deeper customization are locked behind Enterprise quote tiers
Fireflies.ai
Developers who want to skip the transcription and summarization infrastructure and build only the UI layer on top of an existing API
Free (800 minutes storage)
$10/seat/mo (Pro), Business/Enterprise for API access
Quote-based (GraphQL API on Business/Enterprise)
Pros
- +GraphQL API on Business/Enterprise tier allows building a custom frontend
- +Broad meeting platform support and topic tracker features
- +Strong search and snippet-extraction features
- +Established product with extensive review history
Cons
- −The GraphQL API gives you data access, not a rebrandable platform — you're building your own UI on top of their processing anyway
- −No white-label dashboard exists at any published price — Business/Enterprise API is the only path
- −Per-seat pricing on the API tier is not publicly disclosed
- −Building on their API still ties your product to their infrastructure and uptime
Otter.ai
Individual users and teams who want personal AI meeting notes — not relevant for white-label resale
300 monthly transcription minutes
$16.99/user/mo (Pro)
Quote-based
Pros
- +Widely recognized brand — end-users may already trust it
- +Real-time live captions in Zoom/Meet/Teams via the OtterPilot bot
- +Strong transcript editing and highlight features
- +Enterprise has SSO and advanced security controls
Cons
- −No white-label tier exists at any price — this is a dead-end for agency resellers
- −OtterPilot bot joins meetings labeled 'OtterPilot' — same visibility problem as MeetGeek
- −Not relevant to this decision guide except as a category benchmark
AssemblyAI (API build-your-own)
Founders building a custom white-label platform who want built-in PII redaction and compliance features without separate integration work
Free tier with limited minutes
$0.0025/min (Universal-2); Universal-3 Pro $0.0075/min streaming
Pros
- +Best-in-class PII redaction as a native add-on — one API flag removes names, SSNs, emails from transcripts
- +Sentiment analysis, topic detection, and chapter summaries built into the API response
- +SOC 2 Type II certified; HIPAA BAA available
- +Strong accuracy on technical/domain-specific vocabulary
Cons
- −This is an API, not a white-label SaaS — you are building the full product, not reselling one
- −Universal-3 Pro streaming at $0.0075/min is more expensive than Deepgram Nova-3 at $0.0043/min batch
- −No meeting-bot ingestion — requires separate Recall.ai or self-hosted bot infrastructure
- −Per-minute pricing with no volume discount at lower tiers
The AI stack
Audio transcription has two cost layers: STT (the ingestion cost, dominated by per-minute pricing) and LLM (the summarization cost, dominated by per-token pricing for long transcripts). At 1 hour of audio, Deepgram Nova-3 batch costs $0.26 and Claude Sonnet 4.6 summary costs $0.08 — total $0.34 per meeting, against $25 ARPU for a 86% gross margin.
Speech-to-text (STT)
Converts audio to text with word-level timestamps and optional speaker diarization
Deepgram Nova-3
$0.0043/min batch PAYG; $0.0077/min streaming; diarization +~$0.12/hrDefault production model for batch transcription on all tiers; streaming for live captioning
OpenAI GPT-4o-mini-transcribe
$0.003/minFree tier transcription; bulk processing where cost dominates accuracy requirements
AssemblyAI Universal-3 Pro
$0.0075/min streaming; Universal-2 $0.0025/min batchLegal, medical, or compliance-sensitive transcription where PII redaction must be guaranteed in the STT step
Self-hosted Whisper large-v3
GPU compute only (~$0.06/hr on spot A10G)High-volume operations (>100 hours/day) or data-sovereignty requirements
Our pick: Deepgram Nova-3 batch for all tiers. Add diarization (+$0.12/hr) only for paid tiers where speaker identification is a stated feature. Route free-tier users to GPT-4o-mini-transcribe ($0.003/min). For HIPAA use cases, use Deepgram's BAA path, not the OpenAI consumer API.
LLM summarization
Converts the full transcript into structured summaries, action items, decisions, and blockers
GPT-5.4 mini
$0.75/$4.50 per M tokensDefault paid-tier summaries; most meeting content is not nuanced enough to justify a more expensive model
Claude Sonnet 4.6
$3/$15 per M tokens; cache hit $0.30/MPremium tier — executive meeting recaps, board minutes, legal depositions
Mistral Large 3
$0.50/$1.50 per M tokensEU-based deployments where data residency matters and cost is a priority
Our pick: GPT-5.4 mini as the default. Claude Sonnet 4.6 as the premium tier for executive-level summaries. Mistral Large 3 for EU-residency-required deployments. Cache the system prompt (Anthropic prompt cache at $0.30/M hit) if you use Claude Sonnet 4.6 at scale.
Meeting bot ingestion
Records and streams audio from live Zoom, Google Meet, and Microsoft Teams meetings via a bot that joins the meeting
Recall.ai
~$0.13/hr per meeting botProduction meeting-bot ingestion — the only practical path to a rebrandable bot without self-hosting a complex WebRTC stack
Our pick: Recall.ai for all production meeting-bot deployments. Self-hosted Zoom RTMP + WebRTC is technically possible but adds 2–4 weeks of engineering for marginal cost savings. At $0.13/hr, Recall.ai costs $1.56 per 12-hour workday of bot runtime — well within the margin of a $25/mo ARPU product.
Storage and delivery
Stores audio files, transcripts (JSON + SRT), and summaries with per-tenant isolation and signed delivery URLs
Cloudflare R2
$0.015/GB-mo storage; $0 egressAll production deployments — the only option with zero egress cost
Our pick: Cloudflare R2 for all storage. Store the original audio, the raw Deepgram transcript JSON, the formatted SRT file, and the LLM summary JSON as separate objects keyed by meeting_id + tenant_id. Auto-expire original audio files after 90 days to manage storage costs.
Reference architecture
The pipeline splits into two paths: file-upload transcription (fully async background job) and live meeting-bot ingestion (real-time Recall.ai webhook stream). The shared bottleneck is the LLM summarization step, which must handle transcripts of variable length (15 minutes to 3+ hours) with consistent output quality.
User uploads audio file OR schedules a meeting for bot ingestion
Next.js frontend + Supabase meetings tableFor file upload: direct R2 upload via presigned URL, stored with tenant_id. For bot: user connects calendar (Google/Outlook OAuth) and selects meetings to auto-record. Meeting row inserted with status=scheduled.
Recall.ai bot joins the meeting and streams audio
Recall.ai webhook → Supabase Edge FunctionRecall.ai fires a webhook when recording starts and when it ends. The recording URL is stored in the meeting row. Bot identity is configured as 'YourBrand Notetaker' — this is the critical rebrand step.
Audio file sent to Deepgram Nova-3 for transcription
Trigger.dev background job → Deepgram Nova-3 APIFor files >30 minutes, chunked submission to Deepgram batch API. For live streams, Deepgram streaming WebSocket. Returns word-level timestamps, confidence scores, and optional speaker labels. Raw JSON stored on R2.
Two-party consent check (for 11 US states)
Supabase Edge Function — state detection logicIf the meeting participants include phone numbers or email domains from CA, CT, DE, FL, IL, MD, MA, MI, MT, NH, or OR, the bot must have announced recording at join. Check the announcement_sent flag; if false, halt and notify the user to re-join with announcement enabled.
LLM generates summary, action items, decisions, and blockers
Trigger.dev → Claude Sonnet 4.6 or GPT-5.4 miniFull transcript sent to LLM with a structured JSON schema: {summary (3–5 sentences), action_items [{owner, task, due_date}], decisions [], blockers [], topics []}. Prompt-cached system prompt reduces cost on repeated calls. Output stored in meetings table JSONB column.
CRM sync (optional phase 2)
Supabase Edge Function → HubSpot / Salesforce / Linear APIAction items pushed to the tenant's CRM as tasks. Decision log appended to the CRM deal/contact record. This is a per-tenant OAuth integration that requires separate setup per CRM platform.
Summary delivered via email and in-app notification
Resend / Postmark + Supabase notification triggerSummary email sent from the tenant's custom domain (via Resend API with custom SMTP). In-app notification creates a notification row in Supabase. Email template includes the tenant's logo and brand color.
Estimated cost per request
~$0.34 per 1-hour meeting: Nova-3 batch $0.0043/min × 60 = $0.26 + GPT-5.4-mini summary ~$0.08 (12K in transcript + 400 out × token rates); Recall.ai meeting bot adds $0.13/hr → total ~$0.47 with bot ingestion
Cost calculator
Drag the sliders to model your actual usage. The numbers update in real time so you can stress-test economics before writing a single line of code.
This model estimates monthly COGS for a white-label transcription service. The dominant variable is total audio hours processed — LLM summarization cost is a fixed fraction (~25%) on top of the STT cost.
Estimated monthly cost
$119
≈ $1,433 per year
Calculator notes
- At 100 users × 20 hrs/mo = 2,000 hrs/mo total COGS: $0.47 × 2,000 = $940 + $110 fixed = $1,050/mo; against $25 ARPU × 100 = $2,500 revenue = 58% gross margin
- Remove Recall.ai cost for upload-only MVP: drops per-hour cost from $0.47 to $0.34, improving gross margin to 73%
- Switch to Claude Sonnet 4.6 for premium tier summaries: adds ~$0.22/hr for transcript-length context — justify with $49+/mo ARPU
- Deepgram diarization add-on (+$0.12/hr) should only be included for paid tiers where speaker identification is advertised — adds ~29% to the STT line
Build it yourself with vibe-coding tools
By Sunday night you'll have an upload-and-transcribe MVP: users upload an MP3, Deepgram Nova-3 transcribes it, Claude Sonnet 4.6 summarizes it, and the result appears in a simple branded dashboard. Live meeting-bot ingestion (Recall.ai) is a phase-2 addition that requires a separate API integration.
Time to MVP
12–16 hours (1 weekend)
Total cost to MVP
$25 Lovable Pro + $20 Deepgram credits + $20 Anthropic credits + Recall.ai trial
You'll need
Starter prompt
Build a white-label AI audio transcription service MVP with these specs: Auth + multi-tenancy: - Supabase Auth (email/password) - Tenants table (id, name, brand_color, logo_url, plan, credit_minutes_remaining) - Meetings table (id, tenant_id, user_id, title, status, audio_url, transcript_json, summary_json, duration_seconds, created_at) - RLS: users can only see their own tenant's meetings Frontend pages: 1. Dashboard — list of meetings with status badges (processing / ready / failed) and meeting duration 2. Upload Meeting — title input + file upload (accept .mp3, .m4a, .wav, .webm) that uploads directly to R2 via presigned URL, then calls the transcribe Edge Function 3. Meeting Detail — transcript panel (searchable text, speaker labels if available) + summary panel (bullets: Summary, Action Items, Decisions, Blockers) + download buttons (TXT, SRT, JSON) Edge Function: transcribe - Accept: meeting_id (the audio is already on R2) - Step 1: Call Deepgram Nova-3 batch API with the R2 audio URL. Enable smart_format and diarize for paid plan tenants. - Step 2: Store the raw Deepgram JSON in transcript_json column and update status to transcribed - Step 3: Send the full transcript text to Claude Sonnet 4.6 with this prompt: 'You are a meeting intelligence assistant. Given this transcript, return a JSON object with: summary (3-5 sentences), action_items (array of {owner, task, due_date?}), decisions (array of strings), blockers (array of strings). Return ONLY valid JSON.' - Step 4: Store the summary JSON in summary_json column and update status to ready - Step 5: Deduct the meeting duration in minutes from the tenant's credit_minutes_remaining IMPORTANT: For large files (>30 min), the Edge Function will time out. For the MVP, add a clear error message: 'Files over 30 minutes are not yet supported — this feature is coming soon.' We will add background jobs in a follow-up prompt. Style: clean professional SaaS UI, Inter font, sidebar navigation with tenant logo in top-left.
Paste this into Lovable
Follow-up prompts (run in order)
- 1
Move the transcription pipeline to a Trigger.dev background job to support files of any length. When the upload completes, instead of calling the Edge Function directly, enqueue a Trigger.dev job with the meeting_id. The job runs the full transcription + summarization pipeline without any timeout constraint. Update the UI to show a processing spinner that polls the meeting status every 10 seconds until status=ready.
- 2
Add Recall.ai meeting bot integration. Add a 'Connect Calendar' button that initiates Google Calendar OAuth (store the refresh token in Supabase per tenant). After calendar connection, show a list of upcoming meetings with a 'Record with AI Notetaker' toggle. When toggled, call the Recall.ai API to schedule a bot to join the meeting. Configure the bot display name as the tenant's company name from the tenants table. When Recall.ai fires the recording_done webhook, trigger the transcription pipeline.
- 3
Add the consent announcement flow for two-party-consent states. Before the bot joins any meeting, check if any participant email domain or phone number area code maps to a two-party-consent state (CA, CT, DE, FL, IL, MD, MA, MI, MT, NH, OR). If so, set a flag on the meeting row and display a warning to the user: 'This meeting includes participants in a two-party-consent state. The bot will announce recording at join. Ensure all participants consent or disable recording.' Log the announcement event with a timestamp.
- 4
Add CRM sync for action items. Add a Settings page where tenants can connect HubSpot (OAuth). After a meeting summary is ready, if the tenant has HubSpot connected and the meeting title matches a deal name or contact name, push action items as HubSpot Tasks assigned to the meeting owner. Show sync status on the Meeting Detail page.
- 5
Add a per-tenant credit system with Stripe billing. Credits are measured in minutes. Add a Buy Credits page with three packages: Starter ($9.99 for 500 minutes), Pro ($24.99 for 2,000 minutes), Business ($49.99 for 6,000 minutes). Wire Stripe Checkout + webhook. Show remaining credits in the dashboard header with a warning at 10% remaining.
Expected output
After starter prompt: an upload-and-transcribe MVP supporting files up to 30 minutes with AI summary. After follow-up prompt 1: unlimited file length via background jobs. After prompts 2–5: full meeting-bot ingestion, consent flows, CRM sync, and credit billing.
Known gotchas
- !Lovable Edge Function 30-second timeout is a hard blocker for audio over 5 minutes — the starter prompt explicitly caps at 30 minutes and uses a background job for production. Do not skip this migration.
- !Deepgram's diarization (speaker identification) feature adds $0.12/hr to your cost — only enable it for paid tiers and display clearly which plan includes speaker labels.
- !Recall.ai meeting bot names are configurable but require approval for branded names — test in the Recall.ai sandbox before configuring the production bot identity as your company name.
- !Two-party consent laws in 11 US states are criminal, not civil. The bot must announce recording at join for meetings with participants in CA, CT, DE, FL, IL, MD, MA, MI, MT, NH, or OR — this is not optional.
- !GPT-5.4 mini may produce inconsistent JSON output on very long transcripts (>60K tokens) — use Claude Sonnet 4.6 with its 1M context for meetings over 2 hours, or chunk the transcript and summarize in sections.
- !Audio stored on R2 accumulates cost at $0.015/GB/mo — a 1-hour meeting at 128kbps MP3 is 57MB. 1,000 meetings/mo = 57GB = $0.86/mo. Add an auto-expire policy (90 days) to avoid unbounded storage growth.
Compliance & risk reality check
Audio transcription services handle recorded speech from real humans in real meetings. The compliance load is moderate but mandatory — two-party consent laws are criminal in 11 US states, and HIPAA applies the moment a medical professional's meeting is recorded.
Two-party consent recording laws (11 US states)
California, Connecticut, Delaware, Florida, Illinois, Maryland, Massachusetts, Michigan, Montana, New Hampshire, and Oregon require that all parties to a communication consent to recording. A meeting bot that joins and records without announcing its presence and obtaining consent from all participants violates these laws. Criminal penalties vary by state but can include misdemeanor or felony charges.
Mitigation: Configure the Recall.ai bot to announce recording at join for all meetings. Add state-detection logic: if any participant's email domain or phone area code maps to a two-party-consent state, enforce announcement mode. Log the announcement event with timestamp and participant list. Display a clear warning in the UI when scheduling recording for meetings with two-party-consent participants.
HIPAA for medical transcription
Any AI platform that creates, receives, maintains, or transmits Protected Health Information (PHI) on behalf of a covered entity is a HIPAA Business Associate and requires a signed Business Associate Agreement (BAA). If a medical professional uses your transcription service to record patient consultations, PHI flows through your system. Without a BAA, this is a per-incident violation with fines up to $1.9M per violation category annually.
Mitigation: Route medical transcription customers through Deepgram's HIPAA BAA path (Deepgram offers a BAA on Enterprise tier). Do not use OpenAI's consumer API for any healthcare-adjacent transcription. Enforce zero-data-retention mode at the API level. Add a checkbox in the tenant onboarding flow: 'This account will process Protected Health Information (PHI)' — this triggers the BAA requirement and routes to HIPAA-compliant infrastructure.
GDPR Art. 17 right to erasure on stored transcripts
Transcripts stored in Supabase and audio files stored on R2 contain personal speech data. Under GDPR, EU users can request erasure of all their data. A deletion request must cascade to: meeting rows in Supabase, audio files on R2, transcript JSON on R2, summary JSON on R2, and any embedding vectors in pgvector. A soft-delete that leaves audio on R2 does not satisfy GDPR right to erasure.
Mitigation: Build a cascade-delete flow: tenant data deletion triggers Supabase Edge Function that iterates all meeting_ids for the tenant, deletes R2 objects (audio, transcript, summary), deletes pgvector embeddings, and then deletes the Supabase rows. Log the deletion event with timestamp. Provide a user-accessible Delete All My Data button in account settings.
PII in transcripts
Meeting transcripts commonly contain names, phone numbers, addresses, SSNs, financial figures, and other PII from natural conversation. If your platform stores transcripts without PII redaction, a breach exposes this data. AssemblyAI Universal-3 Pro has built-in PII redaction; Deepgram Nova-3 does not have a native PII filter.
Mitigation: For sensitive industry deployments (legal, medical, financial), integrate AssemblyAI's PII redaction add-on or use the Presidio open-source PII redaction library on the raw Deepgram transcript before storing. Offer PII redaction as a paid-tier feature — it adds ~$0.002/min to COGS but justifies $5–10/mo in premium pricing.
Build vs buy: the real math
5–7 weeks
Custom build time
$15,000–$22,000
One-time investment
6–8 months
Breakeven vs buying
At 200 users on MeetGeek Business at $17/user/mo, the monthly SaaS cost is $3,400 — $40,800/year. A RapidDev custom build at $15K–$22K with $300–$600/mo infra costs $22,000 + $4,800 = $26,800 in year one, saving $14,000 versus MeetGeek in year one and $36,000/year every subsequent year. But the bigger win is the bot identity: MeetGeek's bot name leaks your stack to every meeting participant. The custom build breaks even in 6–8 months and eliminates the vendor-identity problem permanently. At 500 users, the savings compound to $102,000/year against MeetGeek's per-seat pricing.
Skip the DIY — RapidDev builds the production version
A Lovable MVP gets you a demo. Production needs auth that doesn't leak data, AI calls that don't bankrupt you, observability when models drift, and code you can audit. That's what we ship.
Discovery call (free)
30 minWe map your exact Audio Transcription Service use case: who uses it, target volume, AI model choice, integrations, compliance scope. You get a detailed scope document and fixed-price quote within 48 hours.
AI-accelerated build
5–7 weeksOur engineers use Claude Code, Lovable, and custom tooling to ship 3–5x faster than agencies. You see weekly progress in a staging environment — not a black box.
Launch + handoff
1 weekWe deploy to your infrastructure, transfer the GitHub repo, set up CI/CD and monitoring, and train your team. You own 100% of the source code, prompts, and model configurations.
What you get
Timeline
5–7 weeks
Investment
$15,000–$22,000
vs SaaS
ROI in 6–8 months
30-min call. Fixed-price quote within 48 hours. No commitment.
Frequently asked questions
How much does it cost to build a white-label AI audio transcription service?
RapidDev builds a production-ready white-label transcription service for $15,000–$22,000. The $15K lower bound covers file-upload transcription with Deepgram Nova-3, Claude Sonnet 4.6 summarization, branded dashboard, and Stripe credit billing. The $22K upper bound adds Recall.ai meeting-bot integration, calendar sync, CRM push for action items, HIPAA-compliant routing, and two-party-consent announcement logic. Build timeline is 5–7 weeks.
How long does it take to ship this?
5–7 weeks for a full production deployment with RapidDev. A Lovable weekend build gives you a working upload-and-transcribe MVP in one weekend — but the live meeting-bot integration (Recall.ai) requires an additional week of engineering outside Lovable's scope. The HIPAA and two-party-consent flows add another week for regulated markets.
Can RapidDev build this for my company?
Yes. RapidDev has built multiple audio processing pipelines with Deepgram, AssemblyAI, and Recall.ai, including HIPAA-compliant deployments via Deepgram's BAA path. We handle the Recall.ai bot integration, consent announcement logic, CRM sync, and multi-tenant architecture. Book a free 30-minute consultation at rapidevelopers.com.
Why can't I just use MeetGeek or Fireflies for white-label?
Because neither rebrand the meeting bot. MeetGeek Business at $17/user/mo only brands the summary email — the bot that joins your clients' Zoom calls still shows up as 'MeetGeek Notetaker' in the calendar invite and in the meeting participant list. Fireflies provides a GraphQL API (Business/Enterprise) but no rebrandable dashboard. If your value proposition is 'your brand's AI meeting assistant,' both options immediately expose your stack to clients. A custom build with Recall.ai is the only path to a fully branded bot identity.
What is Recall.ai and why is it needed?
Recall.ai is a meeting-bot infrastructure API that handles the complex task of joining Zoom, Google Meet, and Microsoft Teams meetings programmatically. It abstracts away the platform-specific API differences (Zoom's RTMP stream, Meet's WebRTC protocol, Teams' Bot Framework) behind a single REST API. It supports configurable bot names — so your bot joins as 'YourBrand Notetaker' instead of any vendor brand. The cost is ~$0.13/hr per bot session, which adds $1.56 to the COGS of a full 12-hour recording day — well within the margin of a $25/mo subscription.
Does the bot have to announce that it is recording?
In 11 US states (CA, CT, DE, FL, IL, MD, MA, MI, MT, NH, OR), all parties to a conversation must consent to recording — these are called 'two-party consent' or 'all-party consent' states. A meeting bot that joins and records without announcing itself and getting consent violates these laws. The Recall.ai bot can be configured to announce recording at join and can refuse to join if participants have not been notified. You must implement this logic before launch.
Is the transcription HIPAA-compliant for medical use?
Only if you route through a HIPAA BAA-covered path. Deepgram offers a BAA on Enterprise tier — use Deepgram for any medical-adjacent transcription. Do not use OpenAI's consumer API (whisper-1, GPT-4o-transcribe without a signed BAA) for healthcare use. The BAA must be signed before any PHI flows through the system — and PHI includes the audio of patient consultations, not just explicitly labeled medical records.
Want the production version?
- Delivered in 5–7 weeks
- You own 100% of the code
- AI cost monitoring built in
30-min call. No commitment.
