Real-time judgment, in the flow of the call.
Kairos joins your team's sales calls, listens to the conversation as it unfolds, and surfaces the right move at the right moment. The system reads the prospect's signals, predicts where the deal is going, and shows the rep the question, objection pivot, or competitive position that fits the moment. Sub-second.
The rest of this page explains how that works. The architecture, the methodology layer, and the learning loop that makes every call sharper than the last.
From audio to the move, in under a second.
Kairos joins the call as a meeting bot or listens silently via Chrome extension. Audio chunks stream to a transcription service. The system reads the rolling transcript, runs trigger detection, and fires the move through a real-time inference path tuned for latency.
Every component on the hot path is engineered for speed. Context is pre-assembled. Trigger candidates are pre-warmed. By the time a trigger fires, the system has already done the work. The rep sees the move before the moment passes.
AUDIO CAPTURE
Bot or Chrome extension joins the call
~ instant
TRANSCRIPTION
Streaming transcript with speaker diarization
~300ms
TRIGGER DETECTION
Pre-warmed candidates against rolling buffer
~50ms
CONTEXT ASSEMBLY
Pre-loaded, no DB or RAG calls on hot path
0ms
INFERENCE
Constrained prompt, 15-word output max
~400-600ms
DELIVERY
Chrome extension sidebar plus optional SMS
~50ms
Total under 1 second from audio chunk to the move on screen.
Three layers, one rule: nothing slow during a live call.
The real-time path cannot wait for database queries or knowledge-base lookups. So Kairos runs a three-layer memory architecture, with everything pre-loaded before the first audio chunk arrives.
L1 / HOT
Redis, in-memory, per session
Rolling 60-second transcript buffer. Pre-assembled context for inference. Live call state. Last few surfaced moves for cooldown enforcement. Destroyed when the call ends.
L2 / WARM
Supabase, loaded once at call start
Full deal history, rep profile, MEDDPICC state, competitive intel, target call state. Loaded once at call start, held in memory throughout. Never queried again during the call.
L3 / COLD
Supabase plus sales methodology RAG
Full playbooks, methodology configs, objection patterns, buying signals. Queried before the call starts. Relevant chunks promoted into L2 and L1. Never touched during the live call.
The rule: nothing hits L3 during a live call. Nothing hits L2 more than once.
Calibrated to the methodologies your team already runs.
What Kairos surfaces is not generic AI output. It is calibrated to Challenger Sale, MEDDPICC, and any custom playbook your CRO has built. The system tracks methodology coverage in real time and surfaces the move that aligns with the framework your reps are trained on.
When the system fires, it is because the methodology says to fire. Not because an LLM had a creative moment.
MEDDPICC · ECONOMIC BUYER
20 minutes into call, EB not identified.
Who else at [company] would need to weigh in on a decision like this?
CHALLENGER · TAKE CONTROL
Rep stuck in teach phase, prospect engagement declining.
You mentioned implementation risk earlier. How is that affecting your timeline?
CUSTOM PLAYBOOK · COMPETITIVE
Competitor name detected with 90% confidence.
Worth asking what specifically about [competitor] is on their shortlist.
Read the room. Shape the call.
Most AI sales tools are reactive. Kairos is built to go further. As the reactive layer proves out, Kairos is learning to read where a conversation is heading — moving toward anticipating the objection forming three turns ahead and surfacing the move that reframes the deal before it lands.
Objection prediction.
When the prospect is building toward an objection — switching cost, pricing pushback, vendor risk — Kairos is learning to recognize the pattern early and surface a preemptive question that reframes the issue before it becomes a blocker.
Buying signal detection.
Kairos is moving toward tracking the structural patterns that signal readiness — timeline questions, colleague references, pricing re-engagement — and showing the rep how to capitalize the moment they appear.
Path correction.
Kairos is being built to compare a call's live state against where it should be at that point in the deal stage — and surface the corrective question when a rep drifts off-path, misses MEDDPICC elements, or stalls in the wrong methodology phase.
Every call makes the next call better.
Kairos learns from three signals. Whether the rep used the move. Whether the deal advanced. Whether the prediction came true. Each signal feeds back into rep profiles, the methodology layer, and the underlying pattern library.
The result is a system that gets sharper with every call. Reps with confirmed blind spots get sharper judgment on those dimensions. Objection patterns that do not predict well get suppressed. Buying signals that consistently lead to deal advancement get weighted more heavily.
Over a quarter of calls, Kairos becomes a system tuned to your specific deals, your specific reps, your specific market. The moat widens.
30 days. Your team. Your deals.
Pilot Kairos on real calls with real reps. Decide for yourself whether real-time judgment moves the numbers.