AI Development

Agentic AI Development: Automate Entire Workflows, Not Just Tasks

Agentic AI systems break big goals into steps, assign them to specialised agents, use tools, check their own work and ask a human when it matters. We design and build these systems for real business processes.

From single agents to autonomous workflows

Many business processes involve several steps and decisions: receive an RFQ, understand the drawing, check stock, calculate cost, draft a quote, get approval and send it. Agentic AI connects these steps. A planner agent decides what to do, specialist agents do the work, a reviewer agent checks quality, and humans approve key decisions.

ENGIMANDI builds agentic systems with durable state, clear hand-offs, strong observability and cost control. We use proven orchestration frameworks and connect agents to your systems through MCP servers and APIs, so the system is reliable enough for production, not just a demo.

What you get

  • Workflow analysis & agent design
  • Planner, worker & reviewer agents
  • Tool use via MCP & APIs
  • Long-running, resumable workflows
  • Human-in-the-loop approvals
  • Tracing, evaluation & cost monitoring
  • Security, permissions & audit trails
  • Continuous improvement from feedback
Capabilities

Agentic AI solutions

Multi-step automation across departments.

Multi-Agent Orchestration

Teams of specialised agents that collaborate, delegate and verify each other's work.

RFQ-to-Quote Automation

Read enquiries and drawings, estimate cost, draft quotations and route for approval.

Research & Analysis Agents

Gather data from the web and internal sources, analyse it and write structured reports.

Software Engineering Agents

Agents that write tests, review code, triage bugs and automate DevOps tasks.

Design Automation Agents

Turn requirements into CAD parameters and drive AutoCAD, Revit or SolidWorks automation.

Back-Office Automation

Finance, procurement, HR onboarding and compliance workflows with approvals.

Technology

Agentic AI tech stack

Production-grade orchestration and observability.

LangGraphOpenAI Agents SDKClaude Agent SDKCrewAIAutoGenSemantic KernelMCPA2ATemporalLangSmithLangfusePythonTypeScriptPostgreSQLRedis
Use cases

Typical projects

  • End-to-end RFQ processing for a fabrication company
  • Market research agent team producing weekly reports
  • Accounts payable workflow with 3-way matching
  • Support system that diagnoses, fixes and follows up
  • Design agent that generates Revit families from specs
  • Recruitment pipeline: screen, schedule and summarise
Our process

How we deliver agentic AI

Map

Document the workflow, decisions and exceptions.

Architect

Agent roles, tools, state and approval points.

Pilot

Run on real cases alongside your team.

Harden

Evaluations, guardrails, retries and monitoring.

Scale

Roll out, measure ROI and extend to new workflows.

FAQ

Agentic AI questions

What does "agentic" mean?

Agentic AI systems act with a degree of autonomy: they plan steps, choose tools, observe results and adjust until the goal is reached, rather than just answering a single prompt.

Will agentic AI replace my staff?

In practice it removes repetitive work so your team can focus on judgement, customers and exceptions. We always design human checkpoints for important decisions.

How do you keep costs under control?

We route simple steps to smaller models, cache results, limit loops and monitor token usage per workflow.

Where should we start?

Start with one well-understood, high-volume workflow. Many clients begin with a single AI agent and grow into agentic systems.