Built for your industry

The Problem

Traditional contact center AI works after the call — transcribing, analyzing, then generating insights. Agents get no real-time help. Supervisors see reports hours later. In collections, the problem is worse: code-mixed conversations (Hindi-English, Spanglish) break most ASR systems, and intent classification happens too late to guide the call.

How Whissle Solves It

Whissle provides Instant Intelligence during the call. Intent is detected as the caller speaks — not after transcription. In collections, the system classifies caller disposition in real-time: promise-to-pay, disputes, hardship, already-paid — and triggers the right next action before the agent has to think. For multilingual call centers, Whissle's code-mixed ASR delivers 20.5% WER on Hindi-English vs 34.7% from leading cloud providers, at 3x lower latency.

Key Capabilities

Drop-in: replace your STT endpoint. Same API, richer output. Works with Twilio, Genesys, NICE, or custom telephony. On-prem deployment keeps all call data in your network.

The Problem

Sales managers rely on shadowing calls or reviewing random samples. Call recording platforms transcribe audio but miss the behavioral signals that separate great reps from average ones — speech pace, filler words, emotional arc, confidence patterns. Coaching is subjective and inconsistent.

How Whissle Solves It

Whissle analyzes every sales call with per-utterance metadata — emotion shifts, intent patterns, and speech characteristics. AI coaching scores each call against configurable best practices (opening, discovery, objection handling, close). Reps see their emotion timeline alongside the buyer's, with highlights on what worked and what didn't. Managers get aggregate rep performance with objective, data-backed coaching recommendations.

Key Capabilities

Upload call recordings or stream live audio. Works with any CRM — Salesforce, HubSpot, custom. Self-hosted to keep proprietary sales conversations off third-party servers.

The Problem

Therapy quality assessment requires trained human raters to listen to full sessions and code every utterance against clinical manuals like MISC (Motivational Interviewing Skill Code). A single 50-minute session takes 2-4 hours to code manually. Most sessions are never reviewed. Supervisors rely on therapist self-reporting, and fidelity to evidence-based practices goes unmeasured.

How Whissle Solves It

Whissle extracts behavioral codes during the therapy session — not after. The META-1 model's psychotherapy domain vocabulary classifies each therapist utterance (open questions, simple reflections, complex reflections, affirmations, giving information) and each client utterance (change talk, sustain talk, follow/neutral) in real-time. Session-level fidelity metrics — reflection-to-question ratio, percentage of open questions, MI adherence — are computed automatically. Prosodic features (pitch, pace, pause patterns) supplement lexical analysis, improving behavioral coding accuracy even with noisy audio.

Key Capabilities

Works across behavioral health, counseling centers, substance abuse programs, and clinical training. HIPAA-compatible with on-prem deployment. No session audio leaves your network.

The Problem

Training soft skills — clinical communication, interview technique, language fluency — requires human standardized patients or trained evaluators. They're expensive, inconsistent, and can't scale to hundreds of students practicing simultaneously. Recording-based assessment happens days after the session, when feedback is least useful.

How Whissle Solves It

Whissle powers interactive 3D avatar agents that listen, understand, evaluate, and respond in real-time. The full pipeline — ASR with behavioral action tokens, LLM evaluation, human-quality TTS, and Audio2Face animation — runs on a single GPU. Students practice with lifelike avatars that assess fluency, empathy, communication style, and domain-specific competencies during the interaction. Assessment is immediate, objective, and rubric-aligned.

Key Capabilities

Renders client-side (WebGL/Unity) with server-side intelligence. Integrates with LMS platforms. Full pipeline fits on a single NVIDIA GPU — from edge (RTX 4090) to data center (H200).

The Problem

Control room operators monitor hundreds of cameras and sensors but can only query systems through complex dashboards. Natural-language access to surveillance databases (ANPR, facial recognition, IoT sensors) doesn't exist. Compliance audits are manual. Staff behavior assessments happen quarterly at best.

How Whissle Solves It

Whissle adds a voice-first query layer over existing surveillance and infrastructure databases. Operators speak naturally — 'show me vehicles from gate 3 between 2 and 4 PM' — and the system converts speech to structured queries over ANPR, video, and sensor data in real-time. The same platform monitors staff behavior, flags compliance violations, and detects fatigue through speech patterns.

Key Capabilities

Integrates with existing ANPR databases, video management systems, and computer vision pipelines. Language-agnostic — extends to any monitored site.

The Problem

Language assessment platforms rely on post-processed transcription with generic ASR models that fail on regional accents, slang, and code-mixed speech. Fluency, pronunciation, and tonal analysis require separate models and manual grading. Custom model training takes months and doesn't transfer well to production.

How Whissle Solves It

Whissle delivers speech assessment features in a single pass: fluency scoring (lexical and acoustic), vocabulary range, grammar analysis, tone and emotion detection, confidence measurement, pace analysis, and filler word tracking. Custom models are trained on your domain-specific data — including Indic slang, regional dialects, and tonal variations — and deployed on dedicated infrastructure with full technology transfer.

Key Capabilities

Scalable private deployment on dedicated GPU infrastructure. Custom models trained on your annotated data. Full technology transfer — including models, datasets, and documentation — at project conclusion.

The Problem

Enterprise search is text-only. Users type queries, get keyword matches. Voice adds a natural interface, but most voice search is just ASR feeding text into existing search. The search engine never improves because it doesn't understand the user's intent — just their words.

How Whissle Solves It

Whissle integrates directly with your search index (Solr, Elasticsearch, custom). As the user speaks, structured filters are extracted in real-time — region, date range, priority, entity names. The search query is built incrementally, not after transcription. Results improve because the search engine receives structured semantic queries, not raw text.

Key Capabilities

Connect Whissle to your existing search index. We don't replace your search engine — we make it voice-native and context-aware.

The Problem

Finding what to watch, listen to, or eat shouldn't require scrolling through endless feeds. Voice assistants handle simple commands ('play jazz') but can't handle complex, personal preferences ('something like that cozy movie from last Sunday, with a book rec and nearby dinner spot').

How Whissle Solves It

Whissle's voice discovery combines music, movies, books, and food recommendations in a single ambient interface. One voice query triggers cross-domain, personalized results — with different suggestions based on who's speaking (age, mood, history). Coming soon.

Key Capabilities

Consumer app — coming soon. Built on the same Instant Intelligence platform that powers our B2B solutions.