Turn Voice & Text Into Business Intelligence.

For healthcare, media, and customer experience, we build custom natural language processing (NLP) models that automate medical transcription, analyze sentiment at scale, and convert audio/video assets into searchable data.

Why Generic Speech Tools Fail?

Standard speech-to-text APIs (like Siri or basic Google Cloud) struggle with jargon, accents, and background noise. Relying on generic models creates three critical data gaps:

The Jargon Barrier

The "Jargon" Barrier

Generic AI fails on complex terminology. It hears "heart attack" when the doctor said "myocardial infarction." We train domain-specific models that achieve 99% accuracy on medical and legal vocabularies.

Loss of Context

Loss of Context

A transcript is just words. It doesn't tell you how the customer felt. Our sentiment & tone analysis detects sarcasm, anger, and urgency to flag at-risk accounts instantly.

Data Privacy Risks

Data Privacy Risks

Uploading patient recordings or legal depositions to public cloud APIs violates HIPAA and GDPR. We build private NLP pipelines that process sensitive audio within your secure firewall.

Solutions for Unstructured Data

Medical Speech Recognition

Medical Speech Recognition

For hospitals & EHRs, we build HIPAA-compliant dictation engines that transcribe doctor-patient conversations in real-time. The AI extracts symptoms, medications, and diagnoses to auto-fill the Electronic Health Record (EHR).

Audio & Video Transcription Software

Audio & Video Transcription Software

For media & legal, we automate the grunt work. We build pipelines that ingest hours of interviews, meetings, or body-cam footage. The AI generates time-stamped transcripts with Speaker Diarization (identifying "Who said what").

Sentiment & Intent Analysis

Sentiment & Intent Analysis

Stop guessing what customers think. We analyze voice recordings and chat logs to score "Customer Sentiment" trend lines. The system flags calls where the agent was rude or the customer threatened to churn.

How We Engineer High-Fidelity Text?

Step 1 Acoustic Pre-Processing

Step 1: Acoustic Pre-Processing

Real-world audio is noisy. We apply spectral subtraction and noise-cancellation algorithms to isolate the voice from background hums, improving transcription accuracy by 30%.

Step 2 Custom Acoustic Modeling

Step 2: Custom Acoustic Modeling

We fine-tune models (like OpenAI Whisper or Kaldi) on your specific audio data. If your users have heavy accents or use industry slang, we teach the AI to understand them.

Step 3 Entity Recognition (NER)

Step 3: Entity Recognition (NER)

The AI identifies key data points. In a medical file, it tags [Dosage], [Drug Name], and [Frequency]. In a legal file, it tags [Plaintiff], [Date], and [Liability Amount].

Step 4 Sentiment Logic

Step 4: Sentiment Logic

We use Transformer Models (BERT/RoBERTa) to analyze the context of words, determining if "That's great" was said genuinely or sarcastically based on pitch and phrasing.

Customer Story

Automating Call Analysis with High-Accuracy AI Transcription

Project's Summary

"Our team spent 40 hours a week listening to sales calls to find coaching moments. Folio3 built an automated transcription engine that flags 'Objection Handling' moments and 'Competitor Mentions' automatically." — VP of Sales, Enterprise Software Company Outcomes: 98% Medical Transcription Accuracy 50% Reduction in QA Costs 100+ Languages Supported

Our Tech Stack

Tech-stack
Folio3 AI leverages the world’s most powerful AI frameworks, models, and acceleration platforms to build secure, scalable, and production-ready AI solutions. Our expertise spans generative AI, deep learning, MLOps, and high-performance inference.

Frequently asked questions

Yes. We use speaker diarization. The transcript will clearly label "Speaker A (Doctor)" vs. "Speaker B (Patient)" or "Speaker C (Nurse)" automatically.
Yes. We architect the solution using HIPAA-eligible services (like AWS Medical or Private Cloud). Data is encrypted in transit and at rest, with strict access logging.
Yes, to a degree. Our pre-processing cleans up phone line static and echo. However, extremely garbled audio will have lower confidence scores, which our system flags for human review.
Yes. If we fine-tune a model on your specific vocabulary (e.g., specific manufacturing parts or rare diseases), that model weight belongs to you.

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  • 22+ Years

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+1 408 365-4638
contact@folio3.ai

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6701 Koll Center Parkway, #250 Pleasanton, CA 94566