Our proprietary ASR engine enables both low-latency, real-time transcription and grouped processing for post call, while processing 5M+ daily interactions in customer environments.

1. Proprietary self-serve correction capability enables domain-specific tuning for brand names and business-specific terminology.
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2. Model-based automatic and selective redaction of sensitive information, including PII, PCI, and HIPAA data.

3. Supports diarized language, segment, and speaker detection.

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Trained on high-quality annotated data, our architecture uses an internal evaluation LLM to benchmark each LLM for performance, cost, and use-case fit to ensure the highest quality for every output.

1. LLM optionality allows you to select the best model for each use case, whether it’s Observe.AI’s optimized model, a generic third-party model, or your own homegrown model.
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2. Human-in-the-loop feedback provides complete control over LLM fine-tuning to improve outcomes.
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3. Models are continually updated to further enhance the accuracy and completeness of the results.

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A no-code command center for tailoring AI-powered insights to your business. Quickly configure and deploy enrichments to surface key signals, context, and behaviors across every conversation.

1. Identify key signals, context, or specific behaviors within a conversation via GenAI moments
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2. Group topics based on customer contact reasons (L1-L3)
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3. Highlight crucial conversation details with summarization 
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4. Track dynamic changes in sentiment for both customers and agents throughout any interaction

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