What might be interesting to HN:

Conversation loop: telephony → streaming ASR → LLM tools → calendar/email → TTS, with turn‑taking and barge‑in control. Calendar booking: buffer‑time logic + double‑booking prevention; we expose a minimal function API for “OfferSlots/BookSlot/Confirm.” Multi‑channel capture: unify phone, email, and form leads into one record with transcript + fields (name, date, guest count, budget). Spam filtering: block patterns (e.g., 1‑800s / robocalls) before they hit staff; safe pass‑through rules for VIPs. Evaluation harness: scripted call scenarios (availability, pricing, policy) → check for grounding (answers must be in your docs) → score for correctness, safety, and escalation timing.

What didn’t work:

Over‑eager answers before knowledge ingestion; we now hard‑gate answers on verified sources and otherwise take a message or escalate. Elevenlabs; Latency is way too much to build a human like experience. Confusion on edge cases (“What’s your cancellation policy if…”). We added doc‑first retrieval + fallback to “collect info + route.”

Numbers so far (early, only 6 customers and improving):

Target answer time: sub‑second pickup; 5‑minute first reply on email. Reduction in missed calls and faster tour scheduling are the main wins; happy to share more once data matures.

Privacy/ethics:

Customer content is not used to train our models. Clear consent and recording policies; PII is encrypted at rest and in transit. What I’d love feedback on:

Better offline evaluation for voice agents (beyond happy‑path scripts). Turn‑taking and barge‑in strategies you’ve found to work well. Failure‑mode handling you’d want before trusting an AI with calls.

Link: https://mikla.ai