Build & Deliver Products Faster, with The Power of Agentic AI
Our Agentic SDLC pods plan, build, test, and release your software, while being supervised by named senior specialists, for a fixed monthly cost. No developer seats. No usage meters.
Meet Our Agentic SDLC Service: Build Faster, with Human Supervision
Software delivery has changed. Most organizations haven’t.
Code is not the constraint any more
Leading teams are moving away from hand-written code, speeding up delivery dramatically. The concerns now are direction, review, and accountability.
Build is replacing buy
Technology leaders are reducing recurring SaaS expenditure by developing customized software in house, considering software developer now costs way less than what it did.
Outcomes matter, not output
Shipping features is not the achievement any more. As coding gets dramatically faster, what carries value is the discernment on what to build, and proof that it works.
When product development is faster, a company’s growth journey gets transformed. Our pods deliver that speed, combined with the engineering disciple that makes it safe to rely on.
Agentic SDLC as a Service: an AI-powered Engineering Team You Commission, Not a Tool You License
A complete software delivery pod, ready on day one. AI agents immaculately perform every role an end-to-end software project needs, while being supervised by senior engineers whose names you know.
Analyst Agents
Developer Agents
Test Agents
Release Agents
Human Experts
Review agent output at every stage. Named aQb specialists supervise - a senior product manager reviews plans, senior engineers review code, senior QA review tests, senior DevOps review releases.
Speed is the reward. Discipline keeps it sustainable.
Every pod delivers the same, excellent performance, whatever be the industry.
Proven architecture, tailored to your needs
Every project begins with predefined architecture templates, reinforced across hundreds of deliveries, then tailored to the product instead of reinvented for it.
The right technology at the right place
Stack choices are based on the problem, not fashion. Each component is chosen for the role it plays in your product, and we can defend every choice.
Code quality maintained through persistent expert review
Best of the breed code quality, kept up by continuous review by senior human engineers, not by a linter and good intentions. Each change is noticed by someone accountable.
QA strategy is based on your industry
Testing strategy follows the standards mandated by your sector, from healthcare and life sciences to financial services, and generates the evidence expected by your auditors.
Cybersecurity monitored continuously
Infrastructure, code paths, and dependencies are monitored for any threats throughout the engagement, rather than being scanned once at release.
Behind every claim on this page, is a mechanism you can inspect.
Anyone can say they’re offering “AI + Human Oversight”. Here’s how our solution actually works - including what happens when AI gets it wrong.
The pull request that was declined
Work that’s unable to prove itself within a limited number of attempts never reaches a reviewer. The pipeline denies the pull request and records the reason. The work you see has been thoroughly reviewed and approved by our engineers.
The audit trail
Each prompt, diff, approval, and release is written to a hash-chained, immutable audit trail. Your compliance team can review the whole process, rather than trusting what we say about how the work is done.
Models selected by evidence
We test candidate models on realistic software-delivery tasks before assigning them to a pod, while retaining the failure artefacts. Independent research outlines unsupervised agents fall short on completing complex projects end-to-end. Our human layer exists because we already noted the performance limitations.
Most AI vendors show you their successes. We designed our pipeline to handle what happens if AI fails.
Transparent pricing that you can read before you talk to us
Three fixed monthly lines, agreed by both before the month starts. No developer seats. No usage meters. No token charges, ever.
Human oversight
Per senior reviewer, per month. The named senior specialists are accountable for approving plans, reviewing code, verifying tests, and signing-off releases.
Agent pod
Our AI agent team in place plans, develops, tests, and releases. Agent count changes with your workload, within your commissioned capacity.
AI infrastructure
Our dedicated hardware serves open weight models, sized to your engagement. Frontier model routed only as per your choice.
More agent activity doesn’t mean more model spend.
Minimum three-month engagement. Pod and infrastructure fees are sized at scoping and stay fixed for the term.
Built for teams whose growth depends on shipping
Some projects prioritize speed, experimentation, and rapid iteration. Others prioritize stability, security, reliability, and predictability. Same pod, same standard, tuned per product. You can choose how conservatively or aggressively the AI agents work. Regardless of what you choose, the human gates are always there.
Product companies and scaleups
Transform your growth trajectory by developing and validating products faster, without needing to scale a large engineering team first. Right from day one, a pod provides you full-lifecycle delivery capacity - at a cost you can plan around.
Often tuned for velocity: short iterations, rapid feedback, with every human gate on.
Technology leaders in established businesses
Extend your existing internal team, work on the projects you’ve kept deferring, and forget about recurring SaaS spend with software you own. Modernise legacy systems and applications while maintaining evidence of the changes, which helps compliance teams to examine well.
Often tuned for assurance: deeper testing, stricter gates, fuller audit evidence.
AI is only as useful as the data behind it
Fragmented data quietly cuts AI’s capability. aQb builds the foundation and the products for AI to deliver optimum performance: data engineering, data warehouses and lakes, knowledge graphs and analytics, connected to the systems your business already operates on.
One engineering partner throughout the journey from data foundation to shipping product. This strong foundation builds product reliability.
Not sure where to start?
The AI Opportunity Audit maps where AI and automation would create the maximum value in your business, what data and integrations it needs, and what to implement first.
One engineering partner, four ways forward
Product engineering
→AI, data and analytics
→Enterprise applications and cloud
→Industry solutions
→From working session to first delivery in weeks, not quarters
Working session
We scope your first workstream together: the product, the standards it must meet, and how your Agentic SDLC pod will be structured to deliver the product.
Commission your pod
Dedicated infrastructure is commissioned for your engagement and the pod is calibrated on real tickets, with end-to-end supervision.
First supervised delivery
Reviewed, tested changes start landing in your repositories, with named senior aQb engineers signing off each stage right from the first ticket.
See a live agent pod at DTX London, ExCeL, 14 to 15 October 2026, Innovation LaunchPad.
Book a working session before the show →Frequently asked questions
It’s a software delivery model in which a pod of AI agents executes the development lifecycle - planning, building, testing and releasing a software product, while named senior specialists review every stage. A product manager reviews plans, engineers review code, QA review tests, DevOps review releases, and remain accountable for quality. It is sold at a fixed monthly cost rather than per developer seat or per token.
AI coding tools help your existing developers code faster, but you still need the team. Contrastingly, agentic SDLC provides the whole delivery capacity itself, with a senior product manager approving plans, senior engineers reviewing pull requests, senior QA verifying tests and senior DevOps signing off releases. You buy outcomes with accountability, not just tool licences.
For most clients, it works alongside the existing team, taking on the projects that have been deferred for long. For product-led companies without engineering, it can be taking on the whole delivery function. Either way, your organisation keeps final approval authority.
The pipeline runs on open weight models hosted on dedicated hardware that are commissioned for your engagement, so day-to-day work carries no per-token charge. Higher agent activity does not create higher model spend. Frontier models can be routed in for specific tasks, but only with your agreement.
aQb Solutions is ISO 27001 certified and has delivered for healthcare and life sciences clients as well as FCA-regulated financial services firms. The service runs in an isolated environment, masks confidential and personal data before any external model call, and writes every prompt, diff and approval to an immutable audit trail.
Repositories and context stay within a dedicated boundary: on premises, our commissioned hardware, or your cloud tenancy. Externally routed tasks, which happen only by your choice, are masked first and run under terms of zero data retention.
Tell us what you are trying to build
Whether you want to deliver a new product, replace your SaaS expenditure with software you own, work on deferred projects, or modernize your legacy systems, a working session will scope the first workstream and the pod to deliver it.
See how a pod works