What We Do
DevAgents OS organizes specialized agents across the software development lifecycle — from discovery to operations — to expand team capacity, reduce rework, preserve context, and create a continuous improvement flow driven by data.
The platform was created to connect AI to the real engineering process, not only to isolated tasks. Each agent operates in a specific stage of the SDLC, shares context with other agents, and contributes to generating technical artifacts, metrics, traceability, and operational visibility.
Agent orchestration across the SDLC
Each stage of the software development lifecycle has its own challenges. Requirements need to be well structured. Architecture needs to record decisions and risks. Code needs to follow standards. Quality needs to be traceable. Security needs to be introduced before production. DevOps needs to reduce delivery failures. Observability needs to explain system behavior. Metrics need to show where the flow gets blocked.
DevAgents OS organizes specialized agents to operate across these stages in a coordinated way.
Instead of using AI as isolated copilots, the platform creates an orchestration layer that connects agents, tools, artifacts, and metrics to the real engineering workflow.
What each agent delivers
Requirements Agent
Supports the transformation of meetings, demands, briefings, and business needs into epics, user stories, acceptance criteria, business rules, and clearer backlog structures.
Architecture Agent
Supports component mapping, technical decisions, architectural risks, integrations, dependencies, solution documentation, and impact analysis.
Code Agent
Supports code generation, review, refactoring, and technical documentation while respecting engineering standards, project context, and team-defined guidelines.
Quality Agent
Supports the creation of test scenarios, Gherkin specifications, automated tests, coverage, evidence, and traceability between requirements, code, and validations.
Security Agent
Supports AppSec activities such as SAST, DAST, dependency analysis, threat modeling, control validation, and risk identification before production.
DevOps Agent
Supports CI/CD pipelines, deployment automation, failure analysis, environment configuration, operational diagnostics, and delivery flow improvement.
Observability Agent
Supports the analysis of logs, metrics, traces, alerts, operational events, and root cause analysis, connecting technical signals to system context.
Metrics Agent
Supports the analysis of lead time, cycle time, throughput, bottlenecks, flow efficiency, predictability, team performance, and continuous evolution.
Modernization Agent
Supports legacy system analysis, business rule extraction, technical documentation, dependency identification, and the definition of paths for gradual modernization.
Governance layer
In addition to specialized agents, DevAgents OS provides a governance layer to connect technical execution, operational indicators, and management decisions.
This layer may support:
- tracking OKRs and engineering goals;
- analyzing team performance;
- monitoring delivery, quality, security, and operational metrics;
- identifying bottlenecks in the flow;
- tracing decisions, artifacts, and outcomes;
- prioritizing improvements;
- providing strategic, tactical, and operational visibility.
The goal is not to create more bureaucracy. It is to turn technical and operational data into visibility for better decisions.
How we operate
DevAgents OS can be used through different models, depending on the organization’s context.
Managed service
DevAgents OS operates or supports the operation of agents, selecting models, providers, integrations, and technical mechanisms appropriate to the contracted scope.
Execution in the client’s infrastructure
The platform can be made available for execution in the client’s own environment, with licensing, validation, authorized components, and integration with the models, tools, and providers defined by the client.
Hybrid model
Combines managed service, licensing, support, updates, specific integrations, and governance according to the organization’s technical maturity, security requirements, and needs.
How we start
The process begins with an assessment of the current engineering flow.
We evaluate where the team loses time, where rework occurs, where decisions get lost, where quality breaks down, where security arrives too late, and where metrics fail to explain what is happening.
Based on this diagnosis, we identify which agents make sense for the real context of the team, which integrations are necessary, and which adoption model is most appropriate.
Expected outcome
DevAgents OS does not seek to replace engineering teams. It expands team capacity by structuring the use of AI within the engineering process.
The expected outcome is a clearer, more traceable, and measurable flow, with agents supporting artifact creation, technical analysis, bottleneck reduction, governance, and continuous improvement.
Contact
To understand how DevAgents OS can support your engineering flow, please use the contact form available on the homepage.
DevAgents OS is a product maintained by PULSEFLOW TECNOLOGIA LTDA.