Multi-agent systems that plan, act, and stay governed.

Specialized agents that collaborate across complex workflows — each with scoped tools, shared memory, and a human gate wherever a decision carries risk.

Start a Project See the approach
agents / run · vendor-reconciliationrunning
6 steps · 1 human gate0 / 6
01 / Problem → solution

Where teams get stuck, and how we engineer past it.

THE PROBLEM
  • 01Single-prompt assistants break down on multi-step work that spans several systems.
  • 02Agents with broad credentials create risk that security teams cannot sign off on.
  • 03Without traces, nobody can explain why an agent took an action.
OUR APPROACH
  • 01Decompose work across specialized agents coordinated by a supervisor with shared state.
  • 02Give each agent least-privilege tools behind an orchestration layer that enforces scope.
  • 03Insert human approvals at consequential steps and record every action with a trace.
02 / What we build

What a agentic systems engagement delivers.

01

Agent architecture

Supervisor, worker, and reviewer roles designed around your workflow.

02

Tool layer

Typed, permissioned tool interfaces to your internal APIs and SaaS systems.

03

Memory & state

Short- and long-term memory with clear retention and access rules.

04

Evaluation

Scenario suites that test plans, tool use, and outcomes before release.

05

Observability

Traces for every step, tool call, and approval decision.

06

Operations

Runbooks, rollback paths, and cost controls for production use.

TECHNOLOGY
  • LangGraph
  • Anthropic
  • OpenAI
  • PostgreSQL
  • OpenTelemetry
03 / Representative solutions
REPRESENTATIVE SOLUTION

Multi-agent engineering system

04 / 06
PROBLEM
Incident triage required senior engineers to correlate logs, deploys, and code changes by hand.
ARCHITECTURE
Specialized agents for logs, traces, deployments, and code, coordinated by a supervisor with shared memory.
WHAT WE BUILT
A triage workflow producing ranked hypotheses and suggested remediation for on-call review.
BUSINESS OUTCOME
Faster diagnosis, with engineers retaining the final decision.
TECHNOLOGYLangGraphOpenTelemetryGrafanaGitHub
REPRESENTATIVE SOLUTION

AI SDLC automation

01 / 06
PROBLEM
Delivery slowed by manual handoffs between ticketing, code review, testing, and release.
ARCHITECTURE
An orchestrator coordinating planning, coding, review, and testing agents over GitHub and CI, with human approval at merge and release.
WHAT WE BUILT
An agent pipeline from ticket to pull request, automated test generation, policy checks, and generated release notes.
BUSINESS OUTCOME
Shorter path from requirement to production, with every agent action reviewable by the team.
TECHNOLOGYLangGraphGitHub ActionsOpenTelemetryPostgreSQL
04 / More solutions

Explore other solutions.

What would you automate if your engineering systems could think?

Tell us the workflow, platform, or operational challenge. Softmatic can help design and build the intelligent system behind it.

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