Copilot accept rate: resolutions shipped without edits, measured from Freshdesk telemetry
FreshworksSolution
The AI support layer SaaS companies run at scale
Sainapse is the AI layer SaaS support teams run inside their existing helpdesk: it decides, drafts, and learns from every resolved ticket instead of just deflecting it. Freshworks, the company behind Freshdesk, runs its own 400+-specialist team on Sainapse, at a 95% copilot accept rate, alongside tools like Freddy AI rather than replacing them.
The economics
Ticket volume outruns headcount long before budget catches up
A SaaS support team's ticket count tracks its customer base, not its headcount plan, and the two curves diverge earlier than most roadmaps admit.
Every resolved ticket also becomes an asset instead of a cost: a decision the team already made once, that the layer can reuse the next time a similar ticket arrives, rather than a transcript nobody reopens. Freshworks measured a +35% shift in CSAT, concurrent with the Sainapse rollout: a correlation, not a formally attributed causal claim, but consistent with quality holding as ticket volume grows.
Triage and routing accuracy: every ticket classified and routed, no specialist in the loop
Customer-initiated touchpoints per resolved ticket, down from 4 (a 70% collapse in customer effort)
How it works
One layer, installed inside the helpdesk you already run
Embeds natively, no migration
Sainapse installs inside Freshdesk directly (the same UI specialists already work in), with no separate console for agents to learn and no ticket data leaving the systems you already run.
Resolves the ticket, not just the queue
A deflection bot redirects the customer and calls it done. Sainapse decides the resolution, drafts it inside Freshdesk, and closes the loop the way a specialist would: only faster, with every outcome reviewed before it ships.
In their words
Freshworks runs its own support on Sainapse
Freshworks
Murali Krishnan, SVP, Customer Experience
Sainapse is the copilot our 400-strong support team actually uses. 95% of the resolutions it generates ship without edits. Our customers now average just over one touchpoint to close a ticket, down from four. Specialists spend their time on the cases that actually need them.
Runs alongside Freddy AI, not instead of it
Sainapse is not a Freddy alternative. It installs as the decide-draft-learn layer underneath the helpdesk Freddy already sits in, so the team's existing tools work off fresher context instead of competing with a new one.
Three ways SaaS teams try to automate support
Built-in helpdesk AI answers inside one product, and a deflection bot tries to stop the ticket at the door. Sainapse resolves it, wherever the systems of record live.
| Built-in helpdesk AI | Point deflection bot | Sainapse | |
|---|---|---|---|
| What it optimizes for | Faster replies inside one product's own console | Fewer tickets reaching an agent | Tickets resolved, verified against what changed in your systems |
| Where it lives | Locked inside a single helpdesk's UI | A widget bolted onto the front door | A layer across the helpdesk, CRM, and backend systems you run |
| How accuracy is proven | Rarely published beyond a demo | Deflection rate, not resolution rate | Copilot accept rate and triage accuracy, published |
| How it improves | Updates on the vendor's release schedule | Static rules and canned flows | Learns from every reviewer correction on your own tickets |
What it runs on
Native embedFreshdesk: the same UI specialists already use, no separate console
Runs alongsideFreddy AI and the rest of the Freshworks stack, nothing to replace
Human reviewEvery drafted resolution is reviewed and sent by a specialist. Nothing ships to a customer unreviewed.
ArchitectureDecide, draft, learn, improve: the same loop runs on every ticket
Powered byAutonomous Resolution · Knowledge from Resolutions · Intelligent Ticket Classification
Common questions
No. Freddy is Freshworks' own AI layer inside Freshdesk, and Sainapse runs alongside it, not instead of it. Sainapse is the decide-draft-learn resolution engine underneath the helpdesk: it classifies tickets, drafts resolutions, and learns from every correction, so the tools your team already uses, Freddy included, work off better information.
A production-grade triage-plus-copilot-plus-knowledge layer is typically a 12-to-18-month build. Sainapse skips that build entirely: the closed loop between triage, drafting, and knowledge is the expensive part, not the models, and model selection, latency, and guardrail work stay off your team's roadmap entirely.
Inside the systems you already run. Sainapse reads and writes through Freshdesk and the platforms it's connected to. It doesn't maintain a separate copy of your ticket data, and nothing a resolution touches leaves your existing systems of record.
Faster than a new hire ramps. Sainapse starts on real tickets in shadow mode, moves to drafting once accuracy holds, and keeps learning from every specialist correction after that; the Freshworks deployment reached its current numbers over twelve months live, not one go-live event.
No. Sainapse embeds inside the Freshdesk UI your specialists already use: no new console to check, no parallel tool, and no migration required before it can start reading tickets.
Related
Where this fits
Automating the full ticket lifecycle
- Autonomous resolution
The shadow-suggest-auto-apply ladder underneath every drafted resolution on this page.
- End-to-end ticket automation
The intake-through-resolution pipeline this layer runs on top of your helpdesk.
Where the knowledge layer comes from
- Knowledge from resolutions
How every resolved ticket becomes new SOPs and calibration instead of a closed ticket.
One customer record across tools
- Cross-system customer context
Merging CRM, helpdesk, and ERP history into the context behind every drafted reply.
Customer support, end to end
- Customer Support workflow
Where this resolution layer sits inside the rest of the support workflow.