NEW Application Knowledge Hub & AI model registry

Every test layer.
One quality signal.

Sakhi-QI Orchestrator unites web, mobile, performance, UI/UX & accessibility and security testing with nine AI QA agents — one platform, one execution ledger and one branded report your clients can trust.

  • Self-hosted with Docker
  • Bring your own AI model
  • Self-healing web & mobile
sakhi-qi / event-managementSQ
WORKSPACE / EVENT MANAGEMENT

Execution overview

Live
Queued04 Waiting for worker
Running02 In progress
Self-healed03 Fixes to review
Run historyCompare
Checkout regressionPlaywright · staging
Passed
Android smoke suiteMaestro · 3 devices
Running
Peak load profileJMeter · performance
Review
Authorised ZAP scanOWASP Top 10 mapped
Done
Quality signal
Results Analyst: 2 failures share one root cause
Locator healedAssertion untouched
Client report readyHTML · PDF · dual logo
PlaywrightMaestroApache JMeterOWASP ZAPSemgrepSchemathesisBrowserStackFirebaseJiraTestRailZephyrConfluenceRedmineGrafanaPostgreSQLRedisDockerWCAG 2.2
5Execution enginesWeb, mobile, performance, UI/UX & a11y, security
9AI QA agentsRequirement analysis through to client reporting
55+Product modulesAcross eight workspaces and admin
8+AI providersPlus any OpenAI-compatible model you register
THE PLATFORM

Five engines and nine agents, orchestrated from one place.

Stop stitching together a separate tool for each test layer. Sakhi-QI runs them side by side on shared infrastructure — with AI doing the heavy lifting and your engineers staying in control.

Playwright

Web automation

Recorder, spec-to-code and API codegen, an autonomous explorer and self-healing locators.

TypeScript & PythonSelf-healingMCP server
Maestro · Android

Mobile automation

Paste test cases, get validated Maestro flows. Run on real devices in parallel or on BrowserStack.

Offline agentReal devices
Apache JMeter

Performance

Run load tests, edit plans in JMX Studio and ask an AI what the numbers mean.

JMX StudioGrafana
WCAG audits

UI/UX & accessibility

Authenticated crawls, design-consistency checks and a three-layer WCAG audit.

VPAT / ACR
OWASP ZAP · SAST · SCA

Security

DAST with OWASP Top 10 mapping, Semgrep static analysis, dependency and secrets scans, and capped API fuzzing — live targets only with server-enforced authorisation.

OWASP Top 10SAST & SCAAuthorised scans only
9 specialists

AI QA agents

From BRD analysis to failure triage and the client report, on the AI model you choose — every output reviewed by your engineers before it is used.

BRD → test casesFailure analysisBring your own model
AI QA AGENTS

Nine specialists for the whole testing lifecycle.

Each agent does one job well and hands its output to the next. Every result can be saved, reloaded, edited and reviewed before it goes anywhere.

  1. 01

    BRD Analysis

    Extract requirements, gaps, risks and ambiguities from BRDs and specs.

  2. 02

    Test Plan

    Test strategy plus BDD scenarios, ready to review.

  3. 03

    Estimation

    Effort estimates broken down by scope and test layer.

  4. 04

    Manual Cases

    Web, mobile and smart-watch test cases with automation feasibility.

  5. 05

    Automation Candidates

    Pick the cases worth automating first, and why.

  6. 06

    Code Generator

    Playwright scripts in TypeScript or Python, downloadable as a ZIP.

  7. 07

    Agent Execution

    Run generated scripts and vision checks on bounded workers.

  8. 08

    Failure Analysis

    Root-cause failing runs and separate defects from flaky locators.

  9. 09

    Reports

    Business-readable summaries for stakeholders and clients.

And an AI assistant wherever you work
Test Results AnalystAsk about any run in plain language. Answers come from that run's actual results.
Ask AI personasA QA expert on every page — test architect, performance, security and more.
Platform AssistantIn-app help grounded in product docs. Collects diagnostics and drafts bug reports for you to file.
Maestro expertAn offline mobile agent plus an AI expert that refines and validates flows.
Performance chatDiscuss results, run catalog scripts and query a 2,900+ document knowledge base.
QA Pilot chatQuestion your UI/UX and accessibility scan findings directly.
EVERY FEATURE

Explore the whole platform, workspace by workspace.

Eight workspaces, the same users, ledger and reports underneath. Pick one to see everything it does.

PLAN WORKSPACE

From requirement to reviewed test case

Turn BRDs, specs and existing test assets into plans, estimates and test cases, grounded in what you already know about each application.

  • Upload PDF, DOCX or Markdown
  • Save and reload any AI result
  • Impact analysis when requirements change

Application Knowledge Hub

Governed, per-application knowledge that grounds AI answers. Permissions are checked before anything is retrieved, and credentials are redacted.

BRD analysis

Pull requirements, risks, gaps and open questions out of business documents.

Test plan & BDD

A test strategy and Gherkin scenarios generated together from the same source.

Effort estimation

Defensible estimates broken down by scope, layer and complexity.

Manual test cases

Web, mobile or smart-watch cases with automation-feasibility scoring for each one.

Update existing cases

When a requirement changes, see which cases are affected and get the proposed updates.

Automation candidates

Rank cases by automation value so the backlog starts with the best return.

AI generation pipeline

BRD → scenarios → test cases → script as one reviewable pipeline, published only when you approve it.

HOW IT WORKS

From requirement
to client-ready report.

Keep the thread from a requirement to a test, a run, a failure and its fix — without losing context between tools.

  1. 01
    Bring your requirements

    Upload BRDs, specs and existing test cases, or pull them from Jira, TestRail, Zephyr, Redmine or Confluence.

  2. 02
    Generate with AI agents

    Analyse, plan and estimate, then produce manual cases, Playwright scripts and Maestro flows for your engineers to review.

  3. 03
    Execute across engines

    Dispatch web, mobile, performance, UI/UX and security runs to bounded workers. Every run lands in one ledger.

  4. 04
    Analyse, heal and report

    Investigate failures with AI, apply reviewed self-healing fixes and publish branded reports.

ORCHESTRATION FLOW

One execution ledger

5 engines online
AI agents & control planeAnalyse · plan · generate · dispatch
WebPlaywright
MobileMaestro · Android
PerformanceJMeter
UI/UX & a11yWCAG audits
SecurityOWASP ZAP
WorkersBounded queues
Evidence & reportsRun history · compare · branded HTML/PDF
AI WITH GUARDRAILS

Built so you can trust what the AI does.

Automation that quietly hides a bug is worse than no automation. These rules are enforced by the platform, not left to good intentions.

Healing fixes locators, never verdicts

A failed assertion is treated as a probable defect. AI fixes that change or remove an assertion are rejected.

Authorised security testing only

Every scan against a live target needs an authorisation confirmation that the server enforces, not just a checkbox.

Fail-closed model policy

If a client isn't allowed a model, the call is blocked — never silently routed somewhere else.

Permission-checked knowledge

The Knowledge Hub checks application, client and sensitivity permissions before it retrieves anything.

Every AI call on record

Who called which model, from which engine, and how many tokens it used.

Offline where it matters

The mobile agent, flow generator and results analyst keep working without an external model.

INTEGRATIONS & MODELS

Works with the tools your teams already use.

Industry-standard engines under the hood, connectors to your test-management and issue-tracking stack, and the AI model of your choice.

AI PROVIDERSClaudeGeminiAzure OpenAIGroqCerebrasOpenRouterOllamaAny OpenAI-compatible API
PlaywrightWeb automation engine
MaestroMobile automation engine
Apache JMeterPerformance testing
OWASP ZAPDynamic security scanning
BrowserStackCloud mobile devices
Firebase App DistributionMobile build source
JiraIssues & requirements
TestRail & ZephyrTest management
RedmineIssue tracking & bug filing
ConfluenceRequirements & documentation
Semgrep · pip-audit · SchemathesisSAST, SCA & API fuzzing
GrafanaPerformance dashboards

Need a connector that isn't listed? Tell us during your demo.

DEPLOYMENT

Your infrastructure. Your data.

Sakhi-QI runs self-hosted, so test data, credentials and reports stay inside your network. Engines run as separate containers with bounded workers, so a heavy load test never slows down the rest of the platform.

Self-hosted with Docker

The whole platform comes up with one Compose command, on your infrastructure.

PostgreSQL + pgvector

One database for users, runs, results and vector search.

Redis-backed workers

Bounded queues and concurrency limits per engine, so heavy runs never starve the app.

One execution ledger

Every job from every engine moves through the same tracked lifecycle.

PLANS

Start with one engine. Scale to all five.

Plans are tailored to your team size, the engines you need and how you deploy. Talk to us for a quote.

ONE APPLICATION

Pilot

Prove the value on one application with a guided rollout.

  • Guided onboarding
  • Engines for your pilot scope
  • AI agents with your own model keys
  • Branded reports from day one
Start a pilot
ORGANISATIONS

Enterprise

For organisations with security, deployment and governance requirements.

  • Self-hosted Docker deployment
  • Application Knowledge Hub
  • AI model registry & audit trail
  • Integration & security review
Contact enterprise

Feature availability per plan is confirmed in your proposal.

FAQ

Questions teams ask first.

Anything else? Drop us a message on WhatsApp, Instagram or Facebook — we'll answer it against your own stack.

Do we have to use all five engines?

No. Most teams start with one or two engines in a pilot and switch on more as they go. Engines share the same users, ledger and reports, so adding one later doesn't mean a new tool to learn.

Which AI models does it work with?

Claude, Gemini, Azure OpenAI, Groq, Cerebras, OpenRouter and Ollama out of the box, plus any OpenAI-compatible endpoint you register. You choose the models, and administrators can restrict which ones each client may use.

Can it run without sending data to an AI provider?

Yes, for key workflows. The mobile test-case converter, the deterministic flow generator and the results analyst's fallback run offline. You can also point the platform at a local model through Ollama.

Will self-healing hide real bugs?

No. Self-healing only repairs locators. A failed assertion is treated as a probable defect, and any AI fix that changes or removes an assertion is rejected. Fixes are recorded for your team to review.

Which mobile platforms are supported?

Android, on real devices over USB or Wi-Fi, in parallel, or on BrowserStack cloud devices. Apps can be pre-installed, uploaded as an APK or pulled from Firebase App Distribution.

How is it deployed?

Self-hosted with Docker on your own infrastructure, with PostgreSQL, Redis and the engines as containers. We talk through sizing and security requirements during your demo.

LET'S TALK QUALITY

One message away from smarter testing.

Skip the forms. Slide into our chats, tell us what you test today, and we'll show you the engines that matter on scenarios close to your own.

  • Live walkthrough, your scenarios
  • Fit check for your stack & integrations
  • Pilot and pricing, no strings attached