Expleo Sophia - AI Test Automation From Requirements to Execution
Expleo Group · Software Development
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
Every QA organisation knows the gap. Analysts write requirements, testers translate them into test cases by hand, and an automation team re-scripts the same cases in a framework nobody else can touch. Information gets lost at every handover, ambiguous requirements slip through to UAT, scripts break with every UI change, and regression cycles stretch from days into weeks.
**Sophia, Expleo's end-to-end test automation platform,** closes that gap in one pipeline. It starts where quality starts: the requirements. Sophia reads them wherever they live (BRDs, PDFs, Word documents, Jira, Azure DevOps, Confluence), flags gaps, contradictions and vague acceptance criteria for an analyst to resolve, then generates complete test cases from the approved baseline - traditional ones with preconditions, steps, expected results and priorities, plus Gherkin (Given/When/Then) scenarios ready for Cucumber or SpecFlow.
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The **platform's execution engine (Teresa)** takes it from there. Low-code authoring turns test cases into executable automation, so testers of all levels contribute without writing code. Steps convert to Playwright (web) and Appium (mobile) scripts deterministically from stored templates - nothing to hallucinate - and OpenAPI/Swagger imports bring API testing into the same platform. Runs dispatch in parallel across multiple agents, scheduled or triggered from CI/CD through a single endpoint. Opt-in AI self-healing repairs brittle locators, and mobile execution works with pCloudy, BrowserStack and webmate.
A **Knowledge Graph** grounds every generated test in your application's entities, rules and relationships, and a reviewer signs off at every stage. The platform is model-agnostic: Amazon Bedrock, Azure OpenAI, Databricks or local LLMs such as Llama 3. Built for regulated QA in banking, financial services and insurance, it deploys self-hosted on AWS, your own cloud VMs, or fully air-gapped on-premises, with PII masking, prompt-injection screening, RBAC and SSO. Data never leaves your estate and is never used to train models. Teams report 30-50% less test design effort, faster regression, and unbroken requirement-to-test traceability.
## How to Engage - From Discovery to Value
Expleo delivers Sophia as a professional service engagement with clearly defined phases:
- **Discovery and Scoping (Week 1-2)** - An Expleo consultant assesses your current QA landscape, requirement sources, automation maturity, and deployment constraints. Deliverable: scoping document with recommended configuration, LLM selection, and integration plan.
- **Pilot Deployment (Week 3-5)** - Sophia is deployed in your environment (AWS, cloud VM, or air-gapped on-premises). A representative requirement set is ingested, test cases generated, and automation executed end-to-end. Deliverable: configured platform instance, pilot test suite with traceability report, and validated CI/CD integration.
- **Full Rollout and Training (Week 6-8)** - Knowledge Graph is populated with your domain model, teams are trained on low-code authoring, and production test suites are established. Deliverable: trained team, production-ready test suites, and operational runbook.
- **Hypercare and Continuous Improvement (Week 9-12)** - Expleo provides hands-on support as teams scale adoption, with reviewer feedback loops refining generated output. Deliverable: adoption metrics report and transition to steady-state support.
Contact Expleo through AWS Marketplace to schedule a discovery call and scope your engagement.
Highlights
Highlighted by the publisher on AWS Marketplace.
One pipeline from requirement to executed test. Sophia validates requirements, generates manual and Gherkin/BDD test cases, then its Teresa engine converts them into Playwright, Appium and API automation and runs them in parallel. Teams report 30-50% less test design effort and faster regression cycles. Engagement includes discovery, pilot deployment, full rollout with training, and hypercare support.
Low-code from end to end with no scripting skills needed. Script generation is deterministic from stored templates so there is nothing to hallucinate. Opt-in AI self-healing keeps suites running when the UI changes. Testers of all levels contribute to automation authoring, eliminating the bottleneck of specialized framework engineers and accelerating time-to-value.
Built for regulated industries including banking, financial services and insurance. Fully self-hosted on AWS, customer cloud VMs or air-gapped on-premises. Model-agnostic (Amazon Bedrock, Azure OpenAI, Databricks, local LLMs), Knowledge Graph grounding, reviewer sign-off at every stage, PII masking, prompt-injection screening, RBAC and SSO. Data never leaves your estate and is never used to train models.
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