AI-assisted development operations
Let AI accelerate the routine code work. Keep developers accountable for what ships.
AI coding assistance and automated checks speed up maintenance, QA and documentation while a developer owns review, safety, edge cases and release decisions.
Named ownership, documented workflows and clear reporting.
Development support
Live workflow
ExecutionAI + automation
ControlHuman-owned
IntelligenceMeasurable
VA20Four7 ownsScoped fixes and maintenance
Your team keepsArchitecture and technical strategy
One operating model
Execution. Control. Intelligence.
Three connected layers keep the work moving without turning automation into another black box.
ExecutionAI agents + automation
Handle the stable, repeatable steps.
ControlHuman owners
Approve, resolve exceptions and own sensitive judgement.
IntelligenceQA + customer signals
Measure quality, workflow health and what users are telling you.
What the workflow can own
What you can get off your plate.
Tests, checks and routine maintenance are strong automation candidates. Architectural decisions and anything touching production judgement are not. We scope the role around that boundary.
Site maintenance
Updates, patches, broken links and routine technical housekeeping handled on a defined schedule.
Front-end delivery
Pages, components and responsive fixes built against your existing designs and standards.
Back-end support
APIs, database work, scheduled jobs and integrations scoped into clear, reviewable tickets.
Bug fixing
Issues reproduced, fixed, tested and documented so the resolution is understandable later.
QA and testing
Cross-browser, device and acceptance checks added before release, not after a customer reports the problem.
Technical documentation
Setup notes, change notes and recurring fixes documented while the context is still fresh.
Execution + control
Automate what is stable. Keep human ownership where judgement begins.
The workflow separates repeatable execution from the moments that require a person. AI agents and automation handle stable steps; a named human owner handles judgement, approvals, exceptions and final accountability.
Development supportWorkflow view
BUG-317ReproducedPatchAI-assistedTestsPassedReviewHuman-owned
ControlReview before mergeOutputDocumented change
Intelligence layer
Do not just run the workflow. See how it performs.
The platform brings AI-agent and human-owner performance, Auto QA, scorecards and operational signals into one view. For customer-facing workflows, it also surfaces sentiment, pain points, feature requests and recurring conversation themes.
Explore the platform →Performance intelligenceLive platform
Create a repeatable quality layer around AI and human execution.
Measure workflow quality, completion and review performance.
See where automation needs human intervention most often.
Track completion, bottlenecks and recurring friction.
What changes
Less manual coordination. More visible execution.
Capacity matters, but the bigger gain is a workflow with clearer ownership, better handoffs and a measurable path from request to outcome.
Work you can actually see
A record of what shipped, what automated checks passed and what a person reviewed before release.
Measurement built in
Because we also build the measurement side, you get a clear record of what was done, what was automated and what a person checked — rather than a monthly summary written by the person being reviewed.
The backlog stays under control
A standing allocation gives recurring maintenance and smaller tickets an owner instead of letting them accumulate.
Senior engineers protect their focus
Routine delivery can move without pulling your most experienced people away from architecture and product decisions.
Knowledge stays with the team
Documented changes and reviewable pull requests reduce the risk of context leaving with one person.
Fits your stackWorks around the systems you already use.
WordPressReactNode.jsPHPPythonLaravelGitJira
How we start
One workflow first. Prove the model, then expand.
We map the work, define what AI can execute safely, place the named human control points and launch with a contained scope before expanding.
Map
Understand the workload and current handoffs.
Design
Define AI execution, named human review and escalation.
Launch
Run the workflow inside your existing systems.
Improve
Use QA and performance signals to refine it.
Questions
Questions before you start
Clear answers before you decide whether the model fits.
Could an AI coding agent do this?+
It can draft fixes and we use it for that. What it cannot do is decide whether a change is safe in your system, or own the consequences if it is not. A developer reviews everything before it merges.
Could AI handle this without a developer?+
It can draft fixes and run the checks. Someone still has to judge whether a change is safe in your codebase, and be accountable when it is not. That person is the role.
What seniority should we expect?+
These roles are best suited to scoped delivery and maintenance work. If the requirement actually needs a senior architect or technical lead, we will say so during scoping.
How does code review work?+
Inside your process. Assistants can work on branches, submit pull requests and follow the review, testing and release flow your team already uses.
Can they work with our existing developers?+
Yes. Development support is designed to sit inside your stand-ups, board, repository and communication channels rather than run as a separate engineering function.
Start with the workload
Ready to stop maintenance eating your engineers?
Tell us what keeps pulling your team off product work. We will scope the support role and the automated checks behind it.