AI and realtime voice integration

How we scope the work

Choose the interaction before choosing a model. A live assistant, a searchable transcript and a background document workflow have different latency, privacy and cost requirements. We define what the model may do and when a person must approve an action.

What the engagement can deliver

• A prototype evaluated against representative tasks and audio conditions.
• A documented data flow, provider integration and server-side usage controls.
• A latency, quality and failure-handling evaluation before rollout.

What acceptance should prove

Evaluate accuracy with a task-specific set, not a polished demo alone. Test silence, interruptions, noise, disconnected networks, provider errors and budget limits. Provider pricing and device support are reviewed during scoping.

Start with the problem you need solved

Send the current product or brief, target platforms, important integrations and a useful delivery window. We use that to propose an initial scope, identify missing evidence and agree what a completed milestone means. Commercial terms and availability are confirmed in the proposal.

Relevant decision guides

• AI app integration: scope a useful workflow before choosing a model
• Realtime voice assistant development: define the conversation contract
• Voice agent prototype: prove the risky interaction first
• Speech-to-text or speech-to-speech: choose an architecture for the task
• Voice latency diagnostics: find where conversational delay begins
• Acoustic echo cancellation: diagnose an assistant that hears itself
• Voice activity detection tuning: avoid clipped and premature replies
• Voice interruption and barge-in: stop audio and preserve the right context