Familiar
Familiar provides an end-to-end duplex speech model for outbound sales calls that listens while it speaks, enabling natural interruptions and real-time conversation. Trained on top-performing sales reps' calls, it mirrors prospect tone, runs discovery, and handles objections, responding in about 350ms. The model runs inside the customer's own VPC, with guardrails and full text/audio inspection for every turn.
- AI Agents
- Artificial Intelligence
- Sales Technology
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Voice agents built on turn-based architectures struggle with interruptions, overlapping speech, corrections, pauses, and background noise, causing friction that makes callers disengage. More than 40% of calls drop in the first 30 seconds before leads are even qualified, and existing systems rely on black-box LLMs that can't be tuned to mirror a prospect, handle pushback, or run discovery like a human seller.
Solution
Familiar offers one end-to-end duplex speech model that listens while it speaks, allowing it to handle interruptions and background voices naturally while reasoning directly over speech rather than reducing it to text. The model is trained on calls from top-performing sales reps, enabling it to mirror a prospect's tone and pace, run discovery instead of reading a script, and handle objections. Developers define workflows, tools, guardrails, and personality while Familiar manages the conversation itself, eliminating the need to assemble separate ASR, TTS, turn-detector, and dialogue harness components. The model responds in about 350 milliseconds and runs inside the customer's own VPC.
Target Audience
Primary customers are teams building voice agents for outbound sales use cases, including lead qualification, appointment booking, and debt collection, who need higher call completion and conversion rates.
Features
- Full-duplex speech model that listens while it speaks, supporting natural interruptions, overlaps, and background voices
- Trained on calls from top-performing sales reps to mirror prospect tone and pace, run discovery, and handle objections
- Reasons over speech directly—including how something was said—instead of relying on text transcripts
- ~350ms response time for real-time conversational flow
- Guardrails that can block a response before the caller hears it
- Runs inside the customer's VPC, with data never leaving their cloud; inspect every turn in text and audio
- No separate ASR, TTS, turn detector, or dialogue harness to assemble—one model handles the conversation
- Coach it or fine-tune on your own calls to improve over time