Understand
Get to know your starting point.
01 · Discovery
Business, product and challenges.
02 · Evidence
Documentation, tooling and metrics.
Connecture IQ
Understand where to improve Quality and where to start
Connecture IQ evaluates how people, processes and tools work across software delivery. We identify friction, risks and opportunities for improvement, and turn them into a prioritized roadmap.
Quality Engineering · Automation · AI · Delivery Flow · Risk
Why Connecture IQ
Software delivery changed. Quality has to change with it.
AI is accelerating how software is designed, developed and shipped. But increasing Development velocity does not automatically increase delivery velocity. When Quality processes, automation, feedback loops and risk controls evolve at a different pace, the constraint simply moves downstream. Connecture IQ helps identify where that is happening and what needs to evolve.
Three questions drive the assessment.
01
What is limiting Quality today?
Identify bottlenecks, handoffs, gaps, technical constraints and sources of unnecessary rework.
02
What should change?
Define the target operating model and the capabilities required to support it.
03
What should happen first?
Prioritize the changes that most improve delivery while respecting risk, context and engineering reality.
Assessment Areas
Quality is a system, not a stage.
Connecture IQ evaluates the capabilities and interactions that influence software Quality across the delivery lifecycle.
The depth of each area adapts to the organization's context, its products and current or planned AI use.
Quality Flow
How work moves between Product, Development and Quality, including handoffs, waiting time, feedback loops and work in progress.
Test Strategy
How testing is designed, prioritized and aligned with product risk.
Automation
Coverage, reliability, maintainability, execution strategy and feedback speed.
Regression
How changes are validated and how regression scope is determined.
AI Adoption
Where AI is already being used, where it can reduce manual work and where governance or standardization is needed.
Quality for AI
How AI-powered systems such as LLMs, agents, RAG and AI workflows are evaluated.
Risk & Traceability
How product risk, requirements, tests, defects and engineering decisions remain connected.
Measurement
Whether current metrics actually explain Quality, flow, capacity and delivery performance.
Three Phases, One Outcome
Understand. Evaluate. Transform.
Evaluate
See how Quality works.
03 · Interviews
We validate how things operate with the team.
04 · Assessment
We assess the Quality Engineering dimensions.
Transform
Define the next changes.
05 · Analysis
We identify causes, risks and opportunities.
06 · Roadmap
We prioritize actions for the first 90 days.
Evidence before hype.
Connecture IQ isn't after a generic maturity score—it's about understanding the Quality system as a whole.
Each finding is grounded in available evidence.
Each recommendation responds to a finding.
Each priority considers the expected impact on business and engineering.
Where evidence is insufficient, we say so.
Outputs
A clear picture of where Quality stands and where it should go next.
Executive Summary
A concise view of the most important findings, risks and opportunities.
Evidence-Based Findings
What was identified, why it matters and what evidence supports it.
Current & Target State
How the current Quality model compares with the proposed future state.
Risk Map
Areas where Quality limitations may affect delivery, reliability or scalability.
Opportunity Map
Where process, automation, AI or engineering changes could improve delivery or reduce manual work.
Ready-to-Apply Improvements
Concrete actions the team can start implementing without a broad transformation program.
Priority Changes
Structural changes sequenced by expected impact, dependencies and context.
90-Day Roadmap
A sequenced plan for the first 90 days of execution — the roadmap's horizon, not a timeline for completing the transformation.
AI changes both sides of Quality Engineering.
AI for Quality
Use AI to improve how Quality works.
Test design
Requirements analysis
Defect intelligence
Automation workflows
Risk analysis
Coverage analysis
Engineering knowledge
CONNECTURE IQ
The assessment methodology behind both directions.
Quality for AI
Apply Quality Engineering to AI-powered systems.
LLM applications
RAG systems
Agents
Copilots
Generative AI workflows
AI-assisted product experiences
The goal is not to add AI everywhere. It is to identify where AI meaningfully improves engineering work and where additional Quality controls are required.
Who it's for
When your engineering grows, Quality needs to keep up.
Connecture IQ helps you understand what's slowing that progress down.
Delivery slows down
Development moves faster than QA capacity.
Validations pile up and delay releases.
Testing demands too much
Regression is largely manual or hard to scope.
Automation exists, but its impact isn't clear.
Visibility is missing to decide
It's unclear where QA time actually goes.
Knowledge stays scattered across people, tickets and tools.
AI adds new challenges
AI is adopted without shared Quality criteria.
AI-powered products need new ways to evaluate them.
For engineering and Quality leaders
CTO
VP Engineering
Head of Engineering
QA / QE Leadership
Technology Leaders
Let's talk about your organization's Quality.
The Connecture IQ assessment delivers a clear diagnosis and a prioritized roadmap. Implementation is arranged separately, on your own or together with Connecture.
Connecture IQ · Intelligent Quality