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Clarity in Chaos

The goal is not just to filter noise. It is to understand it.

AMBIE’s goal is 90-95% accuracy in noisy environments where traditional ASR fails, by learning each environment’s acoustics. That is a goal, not a measured result. Proprietary-model release timing and performance remain unvalidated; here is what runs today.

Acoustic Research Status

AMBIE investigates whether environment-aware adaptation can improve speech recognition under noise and overlapping speech. The live API uses commercial engines. Proprietary models remain research in development; no proprietary-model accuracy result or release date has been established.

The next research artifacts are documented evaluation protocols, held-out noise-condition measurements and comparisons with existing speech models. Cisco Caceres’s AMBIE research agenda.

Where Traditional ASR Fails

✗ Accuracy collapses once the noise floor rises

✗ Noisy ICU environments break standard ASR

✗ Generic models fail in unique environments

✗ Call center conversations blend into chaos

✗ Medical jargon and diverse accents cause errors

How AMBIE Aims to Succeed

✓ Goal: 90-95% accuracy in the same environments, not yet measured

✓ Research question: can equipment-aware adaptation reduce recognition errors?

✓ Evaluate adaptation across held-out acoustic environments

✓ Measure recognition with overlapping speakers

✓ Evaluate terminology and accent coverage on documented datasets

90-95%
Initial research target, not a measured result. Proprietary-model release timing remains unvalidated
Live
Transcribe, translate and summarize today, on commercial engines while our own models are built
Oct 2025
Provisional patent application filed on adaptive, environment-aware recognition

Deployment Directions Under Research

The live service is hosted and uses third-party engines. On-premise, edge and hybrid operation remain research and deployment goals.

On-Premise

Research target: on-premise operation and measured data-handling boundaries

Cloud

Live hosted API; additional cloud deployments require validation

Edge

Research target: resource-constrained edge and mobile inference

Hybrid

Research target: hybrid operation with documented data flows

Built for Challenging Environments

Research targets include difficult acoustic environments; suitability requires workload-specific measurement.

High-Noise Environments

Healthcare ICUs, manufacturing floors, construction sites, kitchens, vehicles

Regulated Industries

Regulated use requires separate security, contractual and compliance assessment; no independent certification is claimed.

Contact Centers

Evaluate transcription quality, latency and operational cost

Edge & Mobile

Field service, retail, logistics, delivery-anywhere mobility matters

Quality & Safety

Inspection, safety monitoring, compliance verification, audit trails

Enterprise Scale

Scaling and deployment requirements assessed per workload

Request Early Access

Join teams exploring acoustic intelligence

Ready to Experience Clarity in Chaos?

Get in touch to hear how AMBIE is working toward its 90-95% goal where traditional ASR fails.

Or email us directly at contact@ambie.ai