Quivly vs. Velaris

Quivly vs Velaris: hours, not a rollout

Velaris puts agents on a knowledge graph a forward-deployed engineer sets up. Quivly runs post-sales the hour you connect your stack, with Radar already on the record.

Live in hours. No forward-deployed rollout.
Onboarding, renewal, and expansion, ready on day one.
Radar for signals your internal tools never see.

Read customer stories

Phased migration — see integrations or book a demo for timelines.

Trusted by teams at

Where they actually differ

Both have health, agents, and MCP. Quivly skips the implementation and adds Radar.

Capability	Quivly	Velaris
Go live in hours	Yes	—Not a focus
Health and risk	Yes	Yes
AI agents	Yes	Yes
MCP for Claude and ChatGPT	Yes	Yes
No implementation project	Yes	—Not a focus
External market signals (Radar)	Yes	—Not a focus
CRM, warehouse, and billing together	Yes	Partial

A check is included. Partial covers part of it. A dash is not the product.

What sets Quivly apart from Velaris?

Velaris is an agent platform you implement. Their engineer scopes your systems, migrates the data, and configures the graph. Quivly is the post-sales system, live in hours: the record, the next play, and Radar.

What is the difference between Quivly and Velaris?

Velaris builds a model of every account so agents can answer, flag risk, and take work on — after an engineer has scoped, migrated, and configured it. They also offer MCP into Claude and ChatGPT. Quivly does not start as that project. Connect sources and the book is running: Actions Feed, Ask Quivly, and Radar, in hours.

What is Velaris best for?

A team that wants an engineer to design a knowledge graph and custom agents, and is willing to make that rollout the project.

What is Quivly best for?

A team that wants the book running this afternoon. Ask across CRM, the warehouse, billing, and support. Agents on onboarding, renewal, and expansion. Radar for the market. You can still shape the work. You do not wait on a rollout to see the first account.

Where do Quivly and Velaris overlap?

Both centralize the account, score risk, run agents, and connect to the tools you have, including MCP. The split is time, and Radar. Assistant access is not the difference.

When should a team switch from Velaris to Quivly?

Switch when the rollout is still an implementation, or when market signals and billing belong next to health. Stay if a custom graph, built for you, is the operating model you want.

Trusted by teams from startups to enterprise post-sales teams.

“Before Quivly, our team spent over half their time on manual data-gathering and spreadsheet wrangling. We saw immediate ROI: within our first two weeks.
Now months in, our CSMs are managing up to 60% more ARR in their books of business compared to before—effectively saving us from needing additional headcount as we scale.”

Robyn Lee

Director of Customer Experience · Mycroft

Why choose Quivly over Velaris?

Customer 360

Connected. Not migrated.

CRM, billing, product, and support in one picture the hour they connect. No graph project before the first account is real.

At-risk · by P(churn)

Signals re-ranked every hour

Live

AccountHP(↓)

Railway

Rescue4 signals

24%

Vercel

Medium2 signals

11%

Supabase

Low1 signal

Resend

Stable0 signals

0.3%

Recent alerts

Vercel: Health 84 → 66 in 2 wks

Slack #customer-success · email digest

Railway: Score crossed below 50

P(churn) 24% · paged CSM

Actions Feed

The play is already there

Onboarding, the save, and expansion run when the signal lands. You are not waiting on an agent someone still has to configure.

Expansion playbooks

Start when expansion signals match

2 live

Account · PlaybookStatusStep

Supabase

Expansion QBR + pricing bands

Gmail · SFDC

Running3 / 4

Vercel

New seats: approval loop

Slack · Cal

Running2 / 3

Railway

API tier — upgrade nudge

In-app · email

Queued0 / 2

Plays log

Slack: #expansion — Supabase QBR sent for review

Automated

Vercel: 12 seats — finance approval draft

Needs approval

In-app: Railway “upgrade API tier” nudge

Automated

Ask Quivly

Ask the record, the same day

Risk, renewal, what changed. Across the warehouse and billing, not after a migration.

Portfolio command center

Heatmap · renewals · team load

Live

Portfolio health heatmap

Segments × regions · warmer tone = more attention needed

EMEA

APAC

LATAM

ROW

Enterprise

Mid-mkt

SMB

Velocity

Lower risk

Higher risk

Renewal risk · ARR at stake

Next 90 days$2.1M

prob.-weighted

91–180 days$890K

181+ days$340K

CSM workload & capacity

A. Kim42/48 accts

J. Park38/45 accts

M. Chen51/50 accts

Radar

Outside the graph

Funding, leadership changes, competitive motion. A model of your internal tools does not see that.

Expansion signals

Ranked for your book · last 30d

Live

Account · signalTypeAction

Supabase

Seats +18 · API calls +42% vs LM

High

+$240K ARR

Vercel

New workspace · 3 envs in 14d

New

Uplift

Railway

Adoption: deploys 2.1× L90

High

+$95K

Resend

Steady usage, cross-sell fit

Med

QBR

Watchlist

Vercel+Supabase: shared expansion cluster

CS + AE · #expansion

Railway crossed usage tier threshold

In-app nudge + Slack

FAQs

How long does Quivly take vs Velaris?

Quivly goes live in hours. Velaris leads with a forward-deployed engineer who scopes systems, migrates data, and configures the AI. That is a rollout.

Does Velaris have AI agents too?

Yes. They run on a knowledge graph, and you can have more built. Quivly’s are the product: post-sales plays, Ask Quivly, and Radar, live in hours. You are not buying a project to assemble that.

Do we need a forward-deployed engineer?

That is Velaris’s published path. Quivly is connect the sources and run the book. No services engagement as the price of the first account.

What about MCP?

Both publish MCP, including Claude and ChatGPT. That is not the difference. Hours, the width of the record, and Radar are.

Live in hours. Not after a rollout.

The customer record, the next play, and Radar. No forward-deployed build.