Synap · Use Cases
Built for the agents you're building.
Five real-world deployments for Synap's memory layer — each with the patterns, problems, and proof your team needs to ship.
Continuity of care, by design.
Your AI agents shouldn't start over every session. Neither should your patients.
Explore the Healthcare use caseA memory built for care
- Persistent patient profilesConditions, allergies, medications, and preferences carry across sessions and agents — structured, queryable, and updated in place.
- Treatment timelinesEvery recommendation tracked through to outcome, so the next clinician knows what's been tried, what worked, and what didn't.
- Emotional continuitySession-to-session awareness of mood, progress, and setbacks — so therapy doesn't reset on Monday.
Patients feel listened to. Clinicians keep their context. Care compounds.
Support that arrives already caught up.
Every ticket carries the full history — across channels, across agents, across time.
Explore the Customer Support use caseContext that travels with the customer
- Every ticket, pre-readPrior conversations, resolutions, and open threads surfaced before the agent types a word. Zero warm-up.
- One memory, every channelChat, email, phone, SMS — whichever channel the customer picks up on, the history is already there.
- Tone and sentiment, trackedThe system knows when the customer is frustrated, loyal, or both. Replies and escalation paths adapt.
Tickets close on the first touch. Customers stop repeating themselves. Your team stops fighting the same fire twice.
Your pipeline, with a memory.
Every conversation, objection, and signal carries forward — so your reps never walk into a deal cold.
Explore the Sales use caseMemory that thinks in pipelines
- Deal history, synthesizedEvery call, email, and message tied to the deal — with the signal extracted, not just the transcript. Stop reading meeting notes; start reading the pattern.
- Handoff without a hiccupA new rep inherits the same context the last one built. Introductions stop starting from zero.
- Pattern-aware sellingWhat's working across similar deals — objections raised, buying triggers pulled, timing that closed — surfaced as you work the current one.
Deals move forward on every call. Handoffs stop costing cycles. The pipeline learns.
Voice that doesn't miss a beat.
Real-time memory for agents that have to sound human — without the pause, the loop, or the "let me check on that."
Explore the Voice AI use caseMemory built for real-time
- Sub-100ms retrievalContext arrives before the agent needs it. No turn-boundary pause, no filler.
- Anticipatory loadingLikely-next-turn memory pre-fetched while the user is still speaking. The agent is already prepared for the question they're about to ask.
- Live correction handlingWhen the user updates a fact mid-turn, memory reflects it before the next response. No "I have you down as…" drift.
The agent keeps tempo. The customer stops hearing the seams. Voice finally sounds like voice.
One memory across every agent.
When one agent learns something, every agent knows it. Shared memory, scoped by default.
Explore the Multi-Agent use caseShared state, sensibly scoped
- A single memory surfaceEvery agent writes to and reads from the same memory layer — episodic, semantic, and factual. Stop duplicating retrieval pipelines per agent.
- Scope isolation by defaultCustomer-scoped, session-scoped, tenant-scoped. Agents share what they should and can't see what they shouldn't — enforced at the infrastructure layer, not the prompt.
- Durable institutional memoryInsights, patterns, and decisions persist across runs. The stack learns from its own work — week over week, not turn over turn.
Your agents stop repeating work. They start building on each other. The stack learns — permanently.
Also supports
Education · E-Commerce · Legal · Financial Services · HR & Recruiting
Whatever your agents do, Synap is the memory layer underneath.
Pick a use case, or talk to us.
Every Synap deployment starts the same way — with the memory model that fits your agents' work.