Nowen
MAMomentic AI logo

Momentic AI Unclaimed

Software Development & QA

Claim this company agentAnalyze as a competitorEvaluate as a vendor

momentic.ai

AI-powered software testing platform helping engineering teams automate end-to-end testing and ship software faster with reliable quality.

Momentic AI provides an AI-powered software testing platform that enables engineering, QA, and DevOps teams to automate end-to-end tests, keep coverage up-to-date, and scale testing as applications grow. It translates plain-language test descriptions into runnable tests in the IDE, integrates with popular development workflows and collaboration tools, and delivers analytics to help teams ship faster with higher quality.

To empower engineering teams to ship faster and with confidence by providing an AI-powered, automated end-to-end testing platform that scales with product complexity.

What we offer

Momentic

Automate Software Testing with AI-Powered Solutions for Reliable Delivery.

momentic.ai/

Market segments

Market size by segment

Growth potential (CAGR)

End-to-end test automation

10.5 Billion USD15% CAGR

Automated generation, execution, and CI-integrated orchestration of full user flows across application surfaces to validate functionality and regressions.

Mobile app testing

8.6 Billion USD13.08% CAGR

Capabilities to run and validate iOS and Android apps at scale on emulators with fast installs, context switching between native and webviews, and no instrumentation.

Shift-left test authoring in IDE

1 Billion USD25% CAGR

Developer- and QA-focused in-editor test creation using plain-language prompts and a copilot to produce runnable tests early in the development cycle.

Autonomous test maintenance

0.8 Billion USD25% CAGR

AI-driven self-healing locators, autonomous test updates, and quarantine workflows that reduce manual maintenance and keep coverage aligned with UI changes.

Test observability and reliability analytics

0.36 Billion USD14% CAGR

Dashboards and failure analysis that surface test performance, flakiness, and trends to prioritize fixes and improve CI reliability.

More information about our offering

Momentic

Momentic is an AI-powered software testing platform that lets engineering, QA, and DevOps teams automate end-to-end tests, keep coverage up-to-date, and scale testing as applications grow. It translates plain-language test descriptions into runnable tests in the IDE, integrates with common development workflows, and provides analytics to help teams ship faster with higher quality.

  • Maintain Tests Seamlessly
    Automatically adjusts test locators to changing UI elements, minimizing the need for manual updates.
  • Speed Up Test Generation
    Automatically creates and updates tests based on app changes, enabling quicker iterations.
  • Generate Runnable Tests Instantly
    Easily create tests by simply describing what you want in natural language, boosting productivity and reducing setup time.
  • Integrate Testing Seamlessly
    This feature allows your AI assistant to interact with tests and modules within your development environment, facilitating immediate feedback and adjustments.
  • Test on Both Platforms
    Utilize a single test suite written in natural language for both iOS and Android.
  • Author Tests Easily
    Empower all team members to contribute to testing without deep technical knowledge.
  • Achieve Robust Coverage
    Utilizes natural language processing to create reliable selectors that endure UI modifications.
  • Simplify Test Creation
    Use natural language to create automated tests without needing advanced coding skills, making testing accessible to all team members.
  • Upload Builds Effortlessly
    Easily upload APKs and IPAs with a single click for streamlined testing workflows.
  • Switch Contexts Smoothly
    Easily transition between native and web contexts for holistic testing.
  • Run Tests Seamlessly
    Conduct tests without the need for app modifications or instrumentation.
  • Simplify Test Creation
    Allows teams to write tests using everyday language, making test creation accessible to all team members.
  • Ensure Test Validity
    Ensures tests automatically update to reflect UI changes, reducing maintenance overhead.
  • Automate Routine Tasks
    Reduce manual effort by allowing AI to handle common test adjustments and confirmations, improving overall efficiency.
  • Install Apps Quickly
    Achieve rapid app installations, significantly speeding up testing cycles.
  • Start Emulators Instantly
    Enjoy quick emulator startup times to enhance feedback loops.
  • Improve CI Stability
    Minimizes interruptions in testing cycles by managing unstable tests effectively.
  • Preview Tests Instantly
    View and iterate on tests directly within the editor for improved efficiency.
  • Optimize Testing
    Facilitates data-driven decision making for continuous improvement in QA processes.

References

Methodology and sourcing behind the figures shown above.

End-to-end test automation

Multiple industry reports in the provided results place the broader automation/test-automation market in the $20–37B range (2023–2025) with consensus CAGRs ~14–17%. End-to-end (E2E) test automation is a sizable subset of that market (tools, orchestration, CI/CD integration and services). Applying a conservative share of ~30–35% of the total automation testing market yields an estimated E2E market of roughly $10.5B today. Given E2E’s close alignment with DevOps/CI-CD, cloud and AI-driven test trends, its growth potential is expected to be in line with or slightly above the overall automation-testing CAGR; estimated ~15% annually.

Mobile app testing

Primary estimate based on Market Research Future (MRFR) which reports a 2024 mobile application testing services market size of $8.6B and a 13.08% CAGR (2025–2035). This is corroborated by other industry reports showing comparable 2024 sizes (~$7.8B) and higher-growth subsegments (mobile application security testing) indicating elevated upside in security and automation areas.

Shift-left test authoring in IDE

Search results show widespread adoption of shift-left testing (IBM, New Relic, Testim, Sauce Labs, Virtuoso, EPAM) but contain no explicit market-size figures. I estimated size by treating ‘shift‑left test authoring in IDE’ as a narrow subsegment of the broader test-automation and developer tooling markets (addressable market: developer IDEs + test automation + emerging AI copilots). Assumptions: a multi‑million developer population with incremental per‑developer SaaS spend for in‑IDE plain‑language test authoring, selective enterprise uptake today, and rapid adoption driven by AI copilots and CI/CD practices. Combining a conservative penetration and pricing model yields a current market estimate ~$1.0B. Growth potential (CAGR ~25%) reflects rapid adoption of AI-assisted authoring, continued shift‑left/CI-CD adoption, and growing automation budgets for QA and developer productivity tools.

Autonomous test maintenance

No direct market-size reports for “autonomous test maintenance” were in the supplied search results. I used analogous published markets for autonomy and automated maintenance/testing (autonomous navigation, predictive maintenance, OTA testing) to size the niche. Autonomous test maintenance is a narrow, high-value slice of the broader software testing and test-automation market (tools + services). Assuming the global software testing/tooling market measured in tens of billions USD, and autonomous self-healing test capabilities represent a small but fast-growing share (roughly 1–3%), a 2025–2026 market size around USD 0.6–1.0 billion is reasonable; I selected USD 0.8B as a midpoint. Growth potential (CAGR ~25%) reflects rapid adoption of AI/ML in DevOps/test automation, higher SaaS pricing for autonomous capabilities, and comparisons to fast-growth adjacent markets (predictive maintenance CAGR ~31%, OTA/autonomy testing CAGRs 7–9%), placing autonomous test maintenance above average software-testing growth but below extreme niche uptakes.

Test observability and reliability analytics

Estimate derived by treating "test observability and reliability analytics" as a narrow subsegment of broader observability and data-observability markets. Industry reports in the searchResults place observability platforms at roughly $11.9B (2026) and data-observability between ~$1.7–2.9B (2024–2025) with CAGRs in the ~11–15% range. Assuming test-focused observability represents ~2–4% of the overall observability tooling spend (reflecting a specialized vertical within developer/CI tooling), 2026 market size ≈ $360M. Growth potential set near the upper range of published CAGRs for observability (14%) reflecting strong DevOps/CI adoption and increasing emphasis on test reliability.

Related Organizations