Solution · Forward deployed engineers
Own the implementation —
and ongoing adoption
One workspace for rollouts through cutover, then a live view of product adoption. An AI agent blends CRM, usage, billing, and market signals so FDEs—and CS—catch nuance early.
| Project | Customer | Owner | Progress | Target date | |
|---|---|---|---|---|---|
Multi-Region Expansion MEDIUMIN PROGRESSON TRACK |  PlanetScale | SCSarah Chan | 100% | Dec 15, 202544d overdue | |
Edge Caching Rollout LOWIN PROGRESSON TRACK |  Fly.io | SCSarah Chan | 67% | Feb 28, 202612d left | |
Postgres Migration HIGHIN PROGRESSAT RISK |  Neon | SCSarah Chan | 40% | Feb 20, 20264d left | |
Private Networking LOWNOT STARTEDON TRACK |  Render | SCSarah Chan | 0% | Mar 10, 202622d left | |
Auth + RLS Review URGENTIN PROGRESSOFF TRACK |  Supabase | SCSarah Chan | 20% | Feb 18, 2026Due today | |
Transactional Email Cutover MEDIUMCOMPLETEDON TRACK |  Resend | SCSarah Chan | 100% | Jan 30, 2026Shipped | |
Redis Cluster Upgrade HIGHON HOLDAT RISK |  Upstash | SCSarah Chan | 55% | Mar 01, 202613d left | |
Preview Deployments LOWIN PROGRESSON TRACK |  Vercel | SCSarah Chan | 82% | Feb 25, 20269d left | |
API Gateway Migration HIGHIN PROGRESSON TRACK |  Cloudflare | SCSarah Chan | 75% | Apr 10, 202615d left | |
SOC2 Compliance Audit URGENTNOT STARTEDAT RISK |  Drata | SCSarah Chan | 0% | May 22, 202645d left |
Proven outcomes
What FDE teams achieve with Quivly
65%
reduction in reactive escalations
4×
faster detection of integration failures
50%
of technical issues resolved before customer notice
3×
more accounts covered per FDE
Implementation
Run repeatable rollouts with one shared implementation timeline
Quivly ties milestones, owners, dependencies, and customer readiness into a single rollout plan — so FDEs and CS stay aligned from kickoff through production cutover, without losing context across tools.
- Milestone templates with dependencies and automatic status rollups
- Customer readiness gates tied to technical checkpoints
- Shared timeline visible to CS and engineering — one source of truth
TOTAL
1
IN PROGRESS
1
COMPLETED
0
OVERDUE
1
Platform Onboarding — Modal
5 days overdue
Implementation
Platform Onboarding — Modal
In progress (2)
QUI-29 Conduct end-user training sessions
MEDIUMSCDue 27 AprQUI-30 Establish success metrics and review cadence
LOWSCDue 8 Apr
Completed (4)
- QUI-25 Complete technical discovery questionnaireHIGHDone 21 Apr
- QUI-26 Set up SSO and team access provisioningHIGHDone 13 Apr
- QUI-27 Configure CI/CD pipeline integrationHIGHDone 31 Mar
- QUI-28 Run initial data migration and validationMEDIUMDone 28 Mar
Proactive intervention
Get ahead of issues — and loop in CS automatically
When Quivly detects a technical risk, it doesn’t just alert the FDE — it routes the right information to the right person. The FDE gets full technical context. The CSM gets a plain-language summary and a suggested customer message. Everyone acts fast, without a coordination call.
- Automatic FDE alert with error logs, affected endpoints, and recommended resolution
- CS-facing summary auto-generated in plain language for customer communication
- Escalation routing to engineering when issues exceed FDE scope
Rollout plan
Modal · single timeline for eng + CS
Discovery
Jan 6
FDE
Integrate
Jan 14
FDE
Validate
Jan 22
FDE · CS
Cutover
Jan 29
CS
Readiness
- Engineering100%
- CS alignment82%
- Security reviewQueued
Cutover gates
- SSO & provisioning
- Migration dry-run
- !Training session
Owner: Sarah Chan · shared with CS lead
"We live in Quivly during rollouts and after go-live. It pulls implementation status, product adoption, and the right external context into one place—so the team isn’t guessing when something looks off."
Shalabh
Head of Customer Solutions Engineering · Union AI
Trusted by post-sales teams at
FAQ
Common questions from FDE teams about Quivly
Quivly can monitor API call volumes and error rates, webhook delivery success and failure, data sync latency and gaps, feature adoption at the endpoint level, SDK and library version currency, and custom technical metrics from your data warehouse. The specific signals depend on what your product emits and which integrations you’ve connected.
Quivly connects to your product analytics layer (Segment, Amplitude, or direct event streams), your observability tools (Datadog, New Relic, or similar), and your data warehouse. It reads the signals you define — Quivly doesn’t need direct access to your production systems. Setup is handled by Quivly’s implementation team with your engineering lead.
Yes, when the data supports it. Quivly can compare error patterns across multiple accounts to detect whether an issue is isolated to one customer (likely their configuration or environment) or affecting a cohort (likely a platform or infrastructure issue). It flags this distinction in the alert so your FDE team knows immediately whether to route to CS or to engineering.
When Quivly detects a technical issue, it simultaneously creates an FDE alert with full technical context and a CS alert with a plain-language summary of what’s happening and a suggested customer message. Both alerts link to the same incident timeline so everyone has the same facts. The CSM can send the customer communication in one click while the FDE works the resolution.
Yes. Beyond error monitoring, Quivly tracks feature adoption at the technical level — which endpoints are being called, which aren’t, which integrations are set up vs. available, and which accounts haven’t enabled capabilities that would drive value. This gives FDEs a proactive agenda for each account: not just ‘what’s broken’ but ‘what’s missing that should be there’.
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