● On-prem audio memory infrastructure
Stop parroting transcripts.
Start building memory.
NoParrot turns every call, meeting and recording into private, agent-ready memory — diarized, searchable, and on your own servers. No cloud. No per-minute API bills.
- ~3% WER (WhisperX large-v3)
- 1.6× realtime on a single GPU
- 5 vector-DB connectors
- MCP-native 6 tools in the MCP server
- 100% on-prem — 0 audio leaves your servers
Your audio archive is dead weight.
- Hundreds of hours of calls, meetings and interviews no one will ever re-listen to.
- Cloud transcription is off the table for anything under NDA, HIPAA or attorney-client privilege.
- ChatGPT can't ingest your recordings. Whisper scripts break on long files and never scale.
From recording to reasoning, in one local pipeline.
- 01
Drop in audio or video
WhisperX + diarization turn it into clean, speaker-labeled text.
- 02
NoParrot structures it into memory
Topic-routed Markdown with metadata, pushed to your vector DB (ChromaDB, Qdrant, Pinecone, Weaviate, or pgvector).
- 03
Your AI agents query it over MCP
Claude, Cursor, or your own SDK. All on your hardware.
MCP server · LangChain Loader · LlamaIndex Reader · any Agent SDK
Vector DB (ChromaDB/Qdrant/Pinecone/Weaviate/pgvector) · diarized, speaker-aware chunking · topic routing · Markdown + YAML
WhisperX large-v3 · pyannote diarization · word-level alignment · multi-language · video OCR · GPU acceleration
Everything the pipeline needs — in one product.
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Diarization that knows who spoke
Speaker labels (SPEAKER_00/01…) embedded in the transcript via pyannote.
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13+ languages
WhisperX large-v3, ~3% WER — including English, Russian, Ukrainian.
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RAG-ready Markdown output
Markdown with YAML metadata, speakers and topics — built for vector DBs.
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Watch-folder automation
Drop a file, get .txt/.srt/.md with a human-readable name in seconds.
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MCP server (6 tools)
Any MCP-compatible agent — Claude, Cursor, your own SDK — queries the memory.
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Audit log & RBAC
Compliance out of the box for Team, Business and Enterprise tiers.
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Web UI + REST API + WebSocket
Upload with progress, full-text history search, batch processing, admin panel.
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Runs on your NVIDIA GPU
6GB+ VRAM (12–16GB recommended). Apple Silicon (MPS) is on the roadmap.
Built for teams that can't send audio to the cloud.
Solo professionals
Drop a folder, ask your AI. On your machine.
AI & engineering teams
MCP-native pipeline. Skip 4–6 months of building.
Law firms, clinics, studios
On-prem, unlimited seats, audit log, BAA-light.
Regulated enterprise
Air-gapped, BAA/DPA, custom diarization, 99.9% SLA.
Private by architecture, not by promise.
Your recordings never leave your infrastructure. No cloud processing, no telemetry without opt-in, no third-party sub-processors for your audio. Full audit log. You hold the data, the model, and the keys.
Build it yourself in 4–6 months — or run it this afternoon.
A production audio→memory pipeline (reliability, diarization, chunked alignment, multi-user, connectors, MCP) is 4–6 months of a senior engineer — $80–150k. NoParrot Team is $1,990/year.
- Build in-house
- $80–150k
- + 4–6 months
- NoParrot Team
- $1,990/yr
- live today
Transparent pricing. Self-serve up to Business.
Free / OSS
$0
Engineers evaluating + students
- CLI + MCP server
- LangChain Loader
- MIT-licensed
- Unlimited local use
Pro Solo
$29 /mo
Solo professional
- Web UI
- Personal RAG chat over your archive
- Auto-configured ChromaDB
- Email support
Pro Team
$199 /mo · 5 seats
Tech teams
- Everything in Pro Solo
- REST + WebSocket API
- All vector-DB connectors
- MCP features, audit log, RBAC
- Slack webhooks
Business
$499 /mo · unlimited seats
Firms of 50–500
- Everything in Pro Team
- SSO (Google / Microsoft)
- Configurable audit retention
- Dedicated email SLA
Enterprise
from $25k /yr
Regulated industries
- Everything in Business
- Air-gapped deployment
- BAA / DPA signed
- Custom diarization & embedding
- On-call support, 99.9% SLA
All tiers run fully on-prem. The Free tier is MIT-licensed and unlimited locally.
Engineering trust
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1800+
automated backend tests
-
Open core
MIT-licensed CLI + MCP server
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Whisper MIT · pyannote CC-BY-4.0
documented model licenses
Questions, answered.
Does my audio ever leave my servers?
No. Processing is 100% local.
What hardware do I need?
An NVIDIA GPU with 6GB+ VRAM (12–16GB recommended). Apple Silicon (MPS) support is on the roadmap.
Which AI agents can use the memory?
Anything MCP-compatible (Claude, Cursor, your SDK), plus LangChain / LlamaIndex and direct vector-DB push.
Is there a free version?
Yes — an MIT-licensed core (CLI + MCP server), unlimited locally.
Can I use it for HIPAA / privileged / NDA content?
Yes — that's the point. On-prem, with audit log; BAA/DPA on Enterprise.
What languages?
13+, including English, Russian and Ukrainian.