How do Devin and QASolve.ai compare in monthly traffic?

Devin has 2,549,346 monthly visits, while QASolve.ai has 0. Traffic estimates describe audience size, not product quality.

How do their growth rates compare?

Devin has a month-over-month growth rate of +1%; QASolve.ai has -100%.

How does pricing compare?

Devin: Paid. Paid, enterprise-oriented. Devin is sold on a per-seat subscription with tiered plans (including higher-capacity tiers for heavier autonomous use) plus usage allowances; Cognition also runs credit programs and enterprise agreements. Because plans and credit packages change, check Cognition's official pricing page for current numbers. QASolve.ai: Paid. Paid, usage-based managed-service plans across three tiers: Standard (ideal for small applications, 50 compute hours, 20 Forward Deployed Engineer hours, Chrome on Linux), Premium or 'Recommended' (medium-size applications, 100 compute hours, 50 FDE hours, all four platform configurations, API access included), and Enterprise (enterprise/ERP applications, unlimited compute, 1 FTE Forward Deployed Engineer included, all platforms, API access, premium support). All plans include unlimited tests, users and runs within the allotted hours; extra compute hours are billed at $15/hour and extra FDE hours at $25/hour. A 30-day money-back guarantee is advertised. Exact plan prices are quoted on demo.

What are alternatives to Devin and QASolve.ai?

Other tools in related categories include Cursor, Manus, Google Antigravity, Replit, Qoder.

Open AI Tools

Devin vs QASolve.ai — Traffic (2.55M vs 0), Pricing & Verdict | Open AI Tools

Head-to-Head Benchmark

Devin vs QASolve.ai

Devin records 2,549,346 monthly visits with +1% month-over-month growth and Paid pricing. QASolve.ai records 0 monthly visits with -100% growth and Paid pricing.

DevinPaidTraffic Leader

Cognition's autonomous software engineer that ships real pull requests

Monthly Visits

2.55M

MoM Velocity

+1%

Top Market

🇺🇸 United States

View Devin Analysis devin.ai

QASolve.aiPaid

Autonomous AI agents that turn your live app into a self-maintaining regression suite

Monthly Visits

MoM Velocity

-100%

Top Market

🌐 Global

View QASolve.ai Analysis qasolve.ai

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	Devin	QASolve.ai
Official Domain	devin.ai	qasolve.ai
Pricing Model	Paid	Paid
Monthly Visits	2.55M (2,549,346)	0 (0)
MoM Traffic Delta	+25.38K (+1%)

Primary Market & Share	🇺🇸 United States (28.1%)	🌐 Global (—)

Direct Visits / mo	1.39M	0

User Rating	4.3	3.9

Supported Platforms	website	Website

Devin

Cognition's autonomous software engineer that ships real pull requests

End-to-end autonomous coding

Devin plans, writes code, runs tests, and opens pull requests across complex, multi-repository codebases without waiting for line-by-line approval.

Its own virtual machines

Devin provisions Windows, Mac, and Linux VMs, builds and runs the project, and tests in a real browser - even recording itself using the feature it built.

Slack, Teams, and alert integration

Mention @Devin in a thread to delegate a fix, or connect CI, PagerDuty, and issue trackers so it reacts to failures and alerts automatically.

Parallel cloud agents

Delegate a large task and Devin splits it across parallel cloud agents that keep working after you close your laptop, then reports back.

Strengths & Pros

+Handles ticket-level autonomous work rather than only suggesting code completions
+Tests in its own browser and VMs, which catches issues that pure code generation misses
+Deep workflow integration with Slack, Teams, CI, and alerting tools
+Keeps working in parallel cloud agents even when your machine is off

Limitations

–Premium, seat-based pricing puts it out of reach for casual individual use
–Complex or poorly specified tasks still need human review before merging
–Maximum value depends on having a well-structured repo and clean test setup

QASolve.ai

Autonomous AI agents that turn your live app into a self-maintaining regression suite

Autonomous UI and journey discovery

Starting only from your application URL, agents map screens, flows and user roles without needing source code, specs or manual scripting, so onboarding does not depend on your engineering team's availability.

Executable knowledge graph

Discovered behaviours are captured in a model of your application's actions, APIs and information structure, letting tests adapt automatically instead of breaking on every UI change.

Continuous execution and self-healing

Suites run on each change and revise themselves as the app evolves, keeping regression coverage trustworthy rather than decaying over time.

Human-in-the-loop triage

Failed and flaky tests are re-run with verbosity enabled, then manually verified by a Success Team, so only validated failures reach your Issues Tracker with reproduction steps.

Strengths & Pros

+No source code or requirement documents needed — testing starts from the running application URL
+Self-healing tests directly address the high broken-test rate that undermines traditional automation
+Human-verified failures with reproduction steps prevent noisy false positives reaching engineers