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Pratap AI Innovations
AI Systems Atlas/Production DeploymentNon-profit & Cultural Archives

Devotional Archive Intelligence

Vishvas Foundation · Panchkula, Haryana

Two decades of recorded Hindi discourse — more than 40,000 files — existed only as audio. We turned it into a searchable, citable corpus running entirely on one machine inside the client's own building, with no recording ever leaving the premises.

Indexed audio

9,402 files (3,015 hrs)

Transcribed with per-word timestamp alignment

Cloud cost

₹0 / minute

100% on-premise execution on local NVIDIA hardware

Data privacy

Air-gapped

Zero audio or transcript data ever transmitted offsite

Devotional Archive Intelligence
System Operational Context · Non-profit & Cultural ArchivesVerified Case Study
01 · The Bottleneck

What was happening inside the operating workflow.

Vishvas Foundation (Panchkula, Haryana) has been recording its founder's discourses for over two decades: 40,000+ files totaling ~12,800 hours. Finding any quote previously required hundreds of hours of manual listening.

Identified Friction Points:

01

Operational Obstacle

More than 40,000 recordings had no text index, making quotation compilations and topic searches virtually impossible.

02

Operational Obstacle

Generic cloud speech models hallucinated over silent periods and lacked accuracy for subtle Hindi spiritual terms.

03

Operational Obstacle

Private devotional recordings could not be sent to third-party cloud APIs on a per-minute meter due to privacy and recurring costs.

02 · Engineering Solution

The connected system that solved it.

A high-reliability architecture with explicit boundary rules, fallback safeguards, and full integration into existing operations.

STAGE 01

Built an acoustic preprocessing pipeline that isolates vocal discourse from harmonium, tabla, hall reverberation, and hiss.

Engineered & Deployed
STAGE 02

Implemented WhisperX large-v3 with wav2vec2 word-level alignment to pin timestamps to every spoken word.

Engineered & Deployed
STAGE 03

Deployed local Ollama language models for supervised Hindi text cleanup and Qdrant/Tantivy hybrid vector search.

Engineered & Deployed
STAGE 04

Packaged the entire pipeline, database, and search UI to run 100% offline on a single on-premise NVIDIA RTX GPU.

Engineered & Deployed
System Stack & Deployment Model

Devotional Archive Intelligence

WhisperX large-v3wav2vec2 alignmentLocal OllamaQdrant + TantivyPostgresNVIDIA RTX 5090

Deployment Scope

Custom Production System

Primary Deliverable

40,000+ recordings indexed on-premise at ₹0 cloud cost with sub-second citations

Governance

100% Human In The Loop

03 · Responsibility Framework

Clear responsibility creates trustworthy AI.

AI handles high-volume retrieval, speed-to-lead, and structured synthesis. People retain complete control over judgment, exceptions, and relationships.

What The AI System Handles

  • Instant sub-minute response & 24/7 coverage
  • Repeatable data structuring, transcription, and qualification
  • Real-time database lookups, vector search, and CRM synchronization
  • Immediate escalation of edge cases and high-priority accounts

What People Control & Decide

  • Setting organizational policies, script boundaries, and approval rules
  • Handling complex exceptions, sensitive disputes, and negotiations
  • Reviewing weekly performance metrics and adjusting system rules
  • Owning executive client relationships and strategic direction
04 · Business Payoff

The measurable difference.

OUTCOME 01

9,402 recordings (3,015+ hours) transcribed, indexed, and made searchable in Hindi and English.

OUTCOME 02

Devotees and editors can ask questions in natural language and receive verbatim text with clickable audio timestamps.

OUTCOME 03

₹0 per-minute cloud API costs with zero confidential audio data ever leaving the foundation's building.

Two decades of discourse turned into a searchable, citable corpus running entirely inside our building without a single byte leaving the premises.

Swami Vishvas · Vishvas Foundation Leadership

Technical Questions

Frequently Asked Questions

How does the Devotional Archive Intelligence system work without cloud APIs?

The entire AI stack—WhisperX for transcription, wav2vec2 for phoneme alignment, Qdrant for vector search, and Ollama for language synthesis—runs locally on an on-premise NVIDIA RTX workstation inside the client's facility.

How accurate are the citations?

Because transcription timestamps are assigned per word rather than per segment, every search citation points to the exact second where the phrase was spoken in the original recording.

Start With Clarity

Have a similar bottleneck in your workflow?

Book a 30-minute AI Readiness Call. We will review your current tools, identify where automation creates measurable ROI, and give you a fixed-scope blueprint.

Discuss This System

30 minutes · No slide deck · Fixed-scope quote