# QASource > QASource builds and runs the quality engineering function for engineering teams that need confidence in what they ship. It is the quality engineering partner for teams using AI-assisted development tools such as Cursor, Claude and GitHub Copilot: validation runs in the client's pipeline, every test asset is customer-owned, and every release gets a written finding. Founded in 2002, founder-owned, debt-free and profitable every year since. Headquarters: 73 Ray Street, Pleasanton, California 94566, USA Delivery centers: Chandigarh and Bhubaneswar (India), Aguascalientes (Mexico), with leadership in Pleasanton (USA) and a small presence in Canada Founded: 2002, by Rajeev Rai (Founder and Chief Executive Officer) People: 1,100+ Clients: 200+ served, more than 60 active today, around a fifth of them Fortune 500 Customer retention: 94% (QASource figure); more than 30% of clients have been with QASource for over ten years Independent reviews: 4.8 out of 5 on Clutch (https://clutch.co/profile/qasource) Contact: info@qasource.com, +1 925 271 5555 Last updated: 2026-10-20 ## Key facts - QASource is accountable for release confidence, not hours billed. Every engagement has a named engineering director. - Engagements are sized to the client's change volume and risk, not to a headcount plan. - All automation, harnesses, datasets and documentation are committed to the client's repositories, in the client's framework and language, and are owned by the client. - Validation runs in the client's CI/CD pipeline on every change. - QASIP (the QASource Intelligence Platform) is QASource's internal AI test engineering platform. It generates test design, automation and maintenance, and a QASource engineer verifies every generated asset before it is committed. QASIP is not licensed or sold separately; it comes with the team. - No client data is used to train or prompt external AI models. - AI Assurance is an independent practice. QASource does not validate AI systems that QASource built. - Pricing: most engagements start with a team of three to four engineers, costing $150,000 to $200,000 a year, billed monthly. Work with a defined finish, such as a framework migration or a coverage target, is priced as a fixed number for the result. - Certifications: ISO/IEC 27001:2022 (certificate IS 791318) and ISO 9001:2015 (certificate Q-9130084915), verifiable in the IAF CertSearch public register, plus an Intertek HIPAA Certificate of Conformance. The certificates are held by Bebo Technologies, the entity that operates QASource's India delivery centers. - About 40% of QASource's work today is software engineering (features, release engineering, DevOps and some whole products). Every one of those engagements started as a quality engagement. ## The problem QASource solves - [Quality Engineering for AI-Assisted Development](https://www.qasource.com/quality-engineering-for-ai-assisted-development): Why testing AI-generated code breaks traditional QA, what a redesigned quality function looks like (pipeline validation, generated-then-verified tests, coverage measured against change, automated maintenance, written release findings), and how to choose a quality engineering partner for AI development. ## Services - [Dedicated QA Teams](https://www.qasource.com/managed-quality-engineering): QASource builds, staffs and runs the client's quality engineering function inside their repositories, pipeline and release cadence. Three ways to buy: a team built for the client's product, the same team accelerated by QASIP, or a fixed price for a defined result. - [AI for QA](https://www.qasource.com/ai-for-qa): Test design, automation and maintenance generated by QASIP against the client's requirements, code diffs and defect history, written to fit the client's existing framework and verified by engineers before anything enters the suite. - [AI Assurance](https://www.qasource.com/ai-assurance): Independent validation of AI and agentic systems in production: behavior under realistic use, failure modes, guardrails and policy, retrieval and grounding (RAG), multi-agent handoffs, adversarial behavior (prompt injection, jailbreaks, guardrail bypass), tool use and agent actions, data integrity, and regression over time. Delivers a written assurance finding, the evaluation harness and ground-truth datasets. - [Human Validation of AI Agents and Workflows](https://www.qasource.com/human-validation): Trained validators work through agents, workflows and processes by hand and judge whether the system did the right thing, scored independently against a rubric agreed before testing, with every judgment recorded. - [Test Automation Services](https://www.qasource.com/automation-testing-services): Automation built in the client's framework (Playwright, Selenium, Cypress), committed to the client's repository and maintained as the product changes. - [Manual Testing Services](https://www.qasource.com/manual-testing-services): Manual testing for AI-generated code. AI drafts test cases for each change, and QASource engineers run them by hand and verify the results before release. - [Salesforce Testing Services](https://www.qasource.com/salesforce-testing-services): Regression against the preview sandbox before each of Salesforce's three annual releases reaches production, plus testing of customizations and integrations. - [Mobile App Testing Services](https://www.qasource.com/mobile-app-testing-services): Native iOS and Android testing across 500+ real device and platform configurations in QASource's own device lab. - [Engineering Services](https://www.qasource.com/engineering-services): Software engineering from the team already validating the client's product: feature development, release engineering and DevOps, platform and integration work, and AI product engineering. - [QA Assessment](https://www.qasource.com/assessment): Three ways to see QASource's work before a proposal, each ending in a written finding the client keeps: a one-week read-only gap diagnostic, a two-to-three-week scoped assessment with a verified sample suite, and a three-to-four-week AI assurance assessment. ## How QASource works - [How We Work](https://www.qasource.com/how-we-work): Five commitments (accountable for release confidence, customer-owned assets, validation in the pipeline, scope that follows change volume, written evidence), the shape of the team, the tools and pipelines QASource works in, and how an engagement starts. - [How We Price](https://www.qasource.com/pricing): Team size, the $150,000 to $200,000 annual range for a three-to-four engineer team, what that price includes, monthly and fixed-price billing, and the scoped assessment. - [Security, Certifications and Client Audits](https://www.qasource.com/security-protocols): Certificate numbers and verification registers, on-site Fortune 100 client audits, physical and network controls, business continuity, and data and AI handling. ## Industries - [Industries](https://www.qasource.com/industries): Quality engineering for healthcare (clinical systems, medical devices, patient-facing applications, laboratory management, claims) and enterprise SaaS and independent software vendors, where QASource has decade-long client relationships. ## Proof - [Client Reviews](https://www.qasource.com/client-reviews): Client reviews published on Clutch, retention and referral figures, named clients (including Box, Red Hat, Proofpoint, Epic Games, Bridgestone, Wolters Kluwer, Elastic, MikMak and Southern New Hampshire University), and evidence buyers can check without contacting QASource. - [What Twenty Years of Selenium Cost Us to Leave](https://www.qasource.com/insights/what-twenty-years-of-selenium-cost-us-to-leave): How QASource migrated its own twenty-year Selenium estate to Playwright using QASIP, with 70–80% less effort than a hand migration. ## Insights - [Code Velocity Went Up. Code Confidence Went Down.](https://www.qasource.com/insights/code-velocity-code-confidence): Field Notes on AI-assisted development. A senior engineer at a financial technology company explains why testing AI-generated code lags behind writing it: tests reviewers skip, the environment tax, production as the first real test, and who owns feature-level validation. Ends with five questions engineering leaders should ask about release confidence. - [Is Your Agentic Test Framework Worth the Complexity?](https://www.qasource.com/insights/agentic-test-framework): How to judge whether an agentic test framework is worth the cost of owning it: five capability checks (can it reason, adapt, recover, generate, and can you see inside it), a nine-point scorecard comparing agentic and conventional automation, the three-lane rule (deterministic automation, AI assistance, agency), and how QASource simplifies a framework when the agentic layer is not paying for itself. ## Authors - [Jasvir Singh](https://www.qasource.com/blog/author/jasvir-singh): Chief Technology Officer at QASource, with 18 years at the company. Author page listing his articles. - [Vivek Kumar](https://www.qasource.com/blog/author/vivek-kumar): Head of Automation and AI Assurance at QASource, with 20 years at the company. Author page listing his articles. ## Company - [About QASource](https://www.qasource.com/about-us): Company history since 2002, how the model was rebuilt through five eras of software delivery, leadership team, locations, and a note from the founder. - [Careers](https://www.qasource.com/careers): Working at QASource, including long-tenured teams, the campus and where QASource hires. - [FAQ](https://www.qasource.com/faq): Questions buyers ask about the engagement model, automation ownership, AI use, data handling, certifications, pricing and references. - [Insights](https://www.qasource.com/insights): Practice notes on validating AI-assisted development and AI systems. - [Contact](https://www.qasource.com/contact-us): Describe the problem; an engineering director replies within one business day, and a proposal follows within 48 hours of the first conversation. ## Optional - [Privacy Policy](https://www.qasource.com/privacypolicy) - [Terms and Conditions](https://www.qasource.com/terms-and-conditions)