Multi-Agent Framework for Software Development
Move faster on your next software project, from first requirements to delivery. Accedia's multi-agent approach speeds up planning, development, and testing while people stay responsible for quality, security, and key decisions.
60%
reduced manual effort
4-8 weeks
to a working MVP, depending on scope
100%
human approval before release
Inside the Document You Will Find
- How the multi-agent approach works: the specialized roles, coordinated workflow and human oversight behind the approach.
- Where people stay in charge: the checks and approvals that keep important decisions under human oversight.
- How it supports your business: less repeated work, shorter delivery timelines, and earlier clarity on project scope.
- A client example: a legacy modernization project completed in 20 calendar days, with identical results across all 131 calculation checks.
What Are the Benefits of AI Agents in Software Development?
Faster delivery. Independent tasks run in parallel, shortening the time from request to working solution.
Less repeated work. Findings carry through each stage, reducing time spent revisiting the same questions.
More confidence in quality. Automated checks help catch problems before they affect users.
Clearer scope from the start. Early discovery identifies requirements and dependencies before development.
Want to See It in Practice?
Explore how Accedia’s multi-agent approach could support your software project.
Our Process in a Nutshell
Each project starts with your goals and the requirements the solution must meet. These guide the tasks assigned to agents, the checks applied along the way, and the points where our team reviews the work.
1
Understand the project
Review your goals, available requirements, and relevant systems to identify gaps and constraints.
2
Agree on the plan
Define the scope, tasks, and expected results, including how the work will be checked.
3
Build and review
Develop the solution in manageable steps, following agreed requirements and quality standards.
4
Check the results
Test that the solution works as intended and that changes preserve existing functions where needed.
5
Engineering approval
Move changes forward only after the required checks and human sign-off.
Get the Full Multi-Agent Workflow Framework
Learn how the approach is structured, what it automates, where people stay in control, and what it produced on a recent project.
Frequently Asked Questions
How do AI agents help speed up software delivery?
AI agents speed up software delivery through volume, handover and parallelism. They read and process a full codebase, its dependencies and its environment far faster than a person can, so the system is understood before work begins. Each agent passes a structured output to the next stage, which removes the repeated investigation that normally happens at every handover. Independent tasks run at the same time, and agents absorb high-volume work that teams skip under pressure, such as test coverage and behaviour comparison.
What types of projects can benefit from multi-agent workflows?
Multi-agent workflows can support new applications, additional features, integrations, and improvements to existing systems. Examples include modernizing a legacy platform, building a customer portal, or connecting business systems to reduce manual data entry. They are particularly useful when work can be divided into clearly defined tasks with results that can be checked. The agent roles and checks depend on the project’s scope, technology, and security requirements.
How does Accedia verify the quality of software developed with AI agents?
We agree on what the software must do and how it will be tested before development begins. Automated tests check the results against those requirements, while separate reviews examine security and technical quality. When updating an existing system, we also check that the functions your business relies on continue to work as expected. Any issues are investigated and resolved, and every change requires human approval before it joins the main codebase.
Do AI agents replace the delivery team?
No. AI agents carry out defined tasks under the delivery team’s supervision, while people remain responsible for key technical decisions, reviews, and approvals. The client works with the team to set priorities, clarify business requirements, and agree on scope changes. By handling repeatable tasks, agents give both teams more time to resolve questions and make decisions that require their expertise.
