Hana Voice AI
Audio-first intelligence that remembers who said what, and when.
System Architecture, ML Pipeline Engineering, Full-Stack Development
2025
Production Architecture / Enterprise Pilot
Target Industry
Enterprise meetings, compliance, knowledge management; India-first workplaces
Core Audience
Enterprise executives, compliance officers, engineering leadership
Stack Foundations
Next.js 16 (App Router), PostgreSQL, Clerk (Multi-Tenant Organizations)
Key Metric
9 Stages
Asynchronous Pipeline
The Problem & The Applied Solution
Fragmented tools, coordination fatigue, and unverified data.
Teams in modern Indian and multilingual workplaces switch fluidly between English, Hindi, and Hinglish mid-sentence. Conventional monolingual tools produce gibberish transcriptions, reset speaker identifiers on every new call, lose critical operational commitments, and silently propagate contradictory statements across corporate wikis.
Autonomous agents, verified state machines, and grounded execution.
A resilient 9-stage asynchronous pipeline: UPLOADED → VALIDATING → PREPROCESSING → DIARIZING_ASR → IDENTITY → UNDERSTANDING → MEMORY → INDEXING → READY. Raw audio undergoes normalization (16 kHz mono PCM WAV, -20 dBFS RMS) and VAD silence stripping, followed by dynamic language routing (en / hi / hi-en). Millisecond word-aligned ASR pairs with Pyannote diarization and 512-dimensional voiceprints. Probabilistic Bayesian identity resolution fuses acoustic and organizational signals to link speech to canonical person entities, updating bi-temporal fact graphs, commitment state machines, and grounded RAG search.
9-Stage Asynchronous Audio Intelligence Pipeline
The audio intelligence pipeline decouples compute-intensive signal processing and machine learning inference from user-facing APIs. Non-blocking state machines process uploaded audio through nine verifiable validation, diarization, identity, and memory ingestion phases.
9-Stage Asynchronous Pipeline & Identity Engine
[ 9 Asynchronous State Stages : Click to inspect transition criteria & invariants ]
DIARIZING_ASR
- Checkpoint 01Dynamic language routing: en / hi / hi-en mid-sentence routing
- Checkpoint 02Whisper prompt conditioning with enterprise vocabulary biasing
- Checkpoint 03Pyannote spectral clustering generating 512-dimensional voiceprints
- Checkpoint 04Millisecond-level word timestamp alignment and confidence scoring
Pipeline Dataflow: Signal → Embedding → Identity → Memory → RAG
Threads Engine
Jaccard overlap & topic decay
Bi-Temporal Memory
Assertion & supersession
Commitment Tracker
Promises with audio proof
Contradiction Engine
Dual-audio conflict cards
Knowledge Graph
kg_nodes & kg_edges JSONB
Signal Normalization: SHA-256 tenant deduplication, 16 kHz mono conversion, and -20 dBFS leveling before any model execution.
Code-Switching Routing: Dynamic routing dynamically dispatches between English, Hindi, and Hinglish vocabulary models with prompt conditioning.
Bayesian Identity Fusion: Weighted scoring (voice 0.45, metadata 0.25, context 0.15, co-occurrence 0.15) maps utterances to persistent canonical profiles.
Bi-Temporal Fact Ledger: Tracks assertion time, system ingestion time, and validity intervals with immutable supersession chains.
Grounded Audio Citations: Every extracted decision, action item, or query response links directly to playable millisecond-accurate audio proof.
Hana Voice AI vs. Generic Transcription Bots
Why commodity meeting recorders fail in multilingual, high-accountability enterprise settings.
| Operational Dimension | Hana Voice AI Architecture | Generic Transcription Bots |
|---|---|---|
| Speaker Identity | ✓Persistent 512-d voiceprints recognizing individuals across meetings. | ✕Generic speaker labels (Speaker 1, 2) that reset on every call. |
| Language Support | ✓Dynamic mid-sentence English / Hindi / Hinglish code-switching. | ✕Monolingual models that fail on multilingual phrases. |
| Organizational Memory | ✓Bi-temporal facts with validity intervals and non-destructive supersession. | ✕Ephemeral transcripts and static, disjointed text notes. |
| Conflict Detection | ✓Automated contradiction engine surfacing dual audio clips for verification. | ✕Silent accumulation of opposing statements across documents. |
| Action Items & Promises | ✓State machine tracking lifecycle with millisecond-exact audio proof. | ✕Unverified markdown bullet lists without ownership accountability. |
| Information Retrieval | ✓Grounded answers with playable millisecond audio citations. | ✕Unverified summaries with potential hallucination risk. |
| Deployment & Privacy | ✓Local / on-premise capable with strict row-level tenant isolation. | ✕Public cloud lock-in with shared database pools. |
Engineered Capabilities & Workflows
Each capability module represents a discrete, type-safe subsystem designed for resilience and performance.
- ✦SHA-256 tenant-isolated hash deduplication preventing redundant processing of identical audio files.
- ✦Lossless FFmpeg audio normalization to standardized 16 kHz mono PCM WAV format.
- ✦RMS dynamic leveling calibrated to -20 dBFS for optimal acoustic model sensitivity.
- ✦Voice Activity Detection (VAD) stripping silence and non-speech artifacts before pipeline ingestion.
- ✦Resilient non-blocking job state machine with automated retry policies and dead-letter queues.
Full-Stack Architecture & Technology Stack
Strictly vetted dependencies ensuring type safety, low latency, and zero vendor lock-in.
Core & Framework
Data & Storage
Multi-Tenancy & Auth
Audio & ML Pipeline
UI & Internationalization
Quality & Observability
Key Engineering Highlights & Outcomes
Asynchronous Pipeline
Zero-blocking processing pipeline from raw WAV upload to indexed knowledge graph.
Voiceprint Embeddings
Persistent acoustic voiceprint clustering that resolves speaker identity across meetings.
Bayesian Identity Fusion
Fuses acoustic similarity, meeting metadata, semantic context, and co-occurrence graphs.
Exact Audio Citations
Every commitment, contradiction, and factual claim links directly to timestamped audio proof.
Visual Workspace & Operational Interfaces
Inspect primary screens, interactive cards, and live operational consoles. Click any image to expand full-resolution view.
Multi-Tenant Audio Intelligence Command Center
1920 × 1080 (16:9)Primary meeting view with waveform player, diarization timeline, participant identity pills, and live transcript follower.
9-Stage Asynchronous Pipeline Telemetry
1600 × 1000 (16:10)Pipeline status monitor showing stage timestamps, deduplication confirmation, language routing score, and diarization status.
Multilingual Code-Switching Waveform Player
1600 × 1000 (16:10)Waveform player demonstrating 0.75x-2.0x playback, speaker turn markers, and aligned Hindi/English words.
Contradiction Engine Dual-Audio Verification
1600 × 1000 (16:10)Dual audio card highlighting opposing budget or timeline claims made across different calls, with resolution actions.
Interactive Postgres Knowledge Graph Traversal
1600 × 1000 (16:10)Relational graph view rendering person nodes, meeting nodes, and commitment edges with multi-hop drill-down.
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