AI-First Quality Engineering

Double your testing throughput

while cutting costs by 80%*

Reliable and accelerated outcomes, contractually committed to your SLAs.
Powered by SNAP™, our model and IDE-agnostic testing platform. See it in action.

*Quality measured as defect leakage between UAT and production. Cost measured
as testing spend as a % of project cost, from ~30% to under 10% at steady state.

What this looks like in practice

2,000 scenarios in 30 min

Velocity

4-6× more scenarios per phase

Coverage

Near-zero defect leakage

Quality

From 800 to under 200
testers

Cost

So why does most testing still look the way it did in 2020?

What we keep hearing from industry leaders

Our releases sit in the QE queue

Engineering output tripled but testing didn’t, so every release waits.

We already use AI for testing

Teams use AI tools, yet quality is flat and headcount remains the same.

Have you seen this month's token bill?

With rising costs of frontier models, a team-wide rollout gets expensive quickly.

Our vendor hasn't suggested AI

They bill per tester. Every dollar they save you comes out of their own revenue.

Our budget isn't shrinking

If your 2026 testing budget isn’t trending toward half of your 2024 budget, you’re overpaying.

Fixing this takes more than a better prompt. It takes an AI-First Testing approach.

AI-First Testing

Powered by SNAP™ Platform

SNAP™ covers the full testing lifestyle with three modules. TestAuthor reads your product and decides what to test. TestAutomate turns those tests into running scripts. TestOrchestrate runs only what each code change could break. Together they take you from a Jira story to a verified release, with your team approving every stage.

Who Uses It?

Built for Product Owners, Functional Consultants, and Testing SMEs who need test coverage that understands their product, plus an automation framework generated for them.

How is it Accessed?

Use it as a standalone platform, inside Jira or Azure DevOps as a native plugin, or from your IDE and coding agent.

Human-in-the-Loop

AI drafts, your experts decide. At every stage, from authoring to automation to orchestration, your team reviews, edits, and approves before anything runs.

Here is how it works in practice
TestAuthor
TestAuthor doesn't just write tests. It learns your product from Jira stories, BRDs, architecture, and UI specifications. Every test is mapped to risk, testing technique, and business intent. So when requirements change, it knows exactly what to test and why.
01
Ingest Context
Jira PRDs UI Specs
02
Ground & Index
Context Lake Architecture Domain Models
03
Agent Execution
Orchestrator Scenario Agents Quality Check
04
Publish
Zephyr qTest Excel
TestAutomate
Converts test cases into automation scripts.
Takes TestAuthor output, converts it to automation-ready format via agent.
Generates automation in standard frameworks.
Bridges the gap between test design and execution, no manual scripting needed.
TestOrchestrate
Executes tests at scale, tuned for an outcome.
Parallel test execution across multiple threads/servers.
Outcome-driven configuration optimized for speed, cost, or coverage.
Customizable execution strategy per client/project, not a rigid fixed pipeline.

See it in practice

How SNAP™ performs against frontier models

We ran the same user story through SNAPTM and through a leading coding agent. Same input, side by side.

SNAPTM
Leading AI IDE
Acceptance-criteria coverage
100%, all 13
85%, 11 of 13
Risk classification
Grounded in TMAP
Free-text, 67% tagged "high"
Model type
General-purpose model (lower cost)
Frontier model (premium cost)
Test cases generated
25
24
How gaps were caught
Context Lake
Code exploration
Tokens used
255,573
2,200,142
Regulatory coverage
Built in: evidence registers, audit trails, maker-checker
NA
Cost of the run
$0.19
$2.15

SNAP™ provides explainable, risk-governed outputs at roughly a tenth of the cost.

One engine. You decide who runs it.

SNAP™ and our pods power both paths. The only difference is who owns it at the end.

We run it

Managed testing. You define the outcome, and we own testing end to end.

We own your testing function and deliver against SLA on SNAP™ , release after release. Quality stops being something you manage.

We build it, you own it

Transformation. We build your testing function, run it until it works, then hand it to your team.

We build AI-first testing on SNAP™ , transfer the tools and knowledge, and leave you a team that runs itself. Own the platform when you’re ready.

Proof, not promises.

Aeroplane in flight

How an international airline built an AI-powered testing function they own and operate independently.

International Airlines deployed SNAP™ across their QA function and took full ownership of the platform. Today, 48 products run through their own AI testing pipeline. The entire function operates inside the airline’s organization.

How a global ecommerce platform improved defect coverage & reduced their testing team from 30 to 6.

Defect leakage fell from 20% to 2% over three years. The testing team reduced from 30 to 6 as AI absorbed routine test execution. As the team size decreased, the capability and coverage of the function increased. 

Testimonials

What our clients say

Why Indexnine

One partner, start to finish.

We assess, transform, and operate. Context, accountability, and outcomes in one place.

Tests built from your product, not generic AI.

Context Lake ingests your BRDs, architecture, Figma, and APIs. Every test reflects your actual product.

Methodology and AI. Not AI alone.

SNAP™ runs on TMAP, 30 years of risk-based testing. Every test traces to a risk level and a business justification.

No lock-in. Ever.

Test cases and scripts live in your environment. The work is yours to keep long after the engagement ends.

Regulatory coverage, built in.

Model- and IDE-agnostic. Evidence registers and audit trails. Maker-checker by design: an independent model checks the maker. The banking control, applied to AI.

Ready to see what this looks like for your product?

A demo that is just 20 minutes. We walk through how SNAP™ works on a product similar to yours, using real test cases and real output. No slides.