AI Voice Analytics Platform — Replacing Enterprise SaaS
A large organization was paying a premium for a rigid SaaS tool to process voice recordings. We built a custom platform that transcribes, summarizes, and indexes audio at scale — cutting costs by 75% while serving 800+ users daily.
75%
Cost reduction vs SaaS
800+
Active daily users
50K+
Audio files processed monthly
<2min
Avg processing time per file
Overview
The client — a large enterprise with thousands of employees — relied on a third-party SaaS platform to transcribe and analyze voice recordings across their operations. The tool was expensive, inflexible, and couldn’t be customized to their specific compliance and reporting needs. Data sovereignty was also a growing concern, as recordings were processed on external servers.
We built a fully custom replacement: an end-to-end voice analytics pipeline that runs entirely on the client’s own infrastructure, processes 50,000+ audio files per month, and serves 800+ daily active users through a purpose-built frontend.
The Challenge
- The existing SaaS cost was growing unsustainably as recording volume scaled — licensing was per-seat and per-minute.
- Audio data contained sensitive information that could not leave the organization’s infrastructure for compliance reasons.
- The SaaS offered limited search, no AI summarization, and no way to build custom reports or dashboards over transcribed content.
- 800+ non-technical users needed fast, intuitive access to recordings, transcripts, and summaries — with role-based permissions.
Our Solution — The Pipeline
We designed a five-stage processing pipeline that takes raw audio and turns it into searchable, summarized, shareable intelligence.
Audio Ingestion
Voice recordings are collected from multiple sources and queued for processing via an async pipeline with retry logic and deduplication.
Speech-to-Text Transcription
Each audio file is transcribed using a self-hosted Whisper model, supporting multiple languages and speaker diarization — with no data leaving the client’s infrastructure.
AI Summarization & Extraction
Transcripts are processed by an LLM to generate structured summaries, extract key topics, sentiment, action items, and flag compliance-relevant content.
Elasticsearch Indexing
Transcripts, summaries, and extracted metadata are indexed into Elasticsearch — enabling full-text search, filtering, aggregations, and real-time dashboards across the entire corpus.
Frontend & Sharing
A custom React UI allows 800+ users to search, browse, listen, and share processed recordings — with role-based access control, saved searches, and export capabilities.
Results
- 75% cost reduction — compared to the previous SaaS, with predictable infrastructure costs that don’t scale per-user.
- Full data sovereignty — all audio, transcripts, and summaries stay on the client’s infrastructure. Zero external data transfer.
- Powerful search & analytics — Elasticsearch enables full-text search across all transcripts, filtering by date, speaker, topic, sentiment, and custom tags.
- AI-powered insights — Automatic summaries, topic extraction, and compliance flagging that the previous SaaS simply could not provide.
- 800+ active users — adopted across the organization within weeks thanks to an intuitive, purpose-built UI with role-based access.
Technology Stack
Paying too much for an inflexible SaaS?
We build custom platforms that outperform off-the-shelf solutions — at a fraction of the cost. Let’s talk.
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