Autonomous Agents

Agents that reason, plan, and act.

Not a chatbot wrapper. Not RPA with a new name. Ovado agents decompose goals into steps, call the right tools, recover from failures, and finish the work — under policies you control.

Multi-step reasoning Multi-agent orchestration Reasoning + action audit trail Human-in-the-loop ready
Agent Anatomy

What's inside an agent

LAYER 01

Reasoning

Understands the goal, weighs the options, and decides the next move — with confidence thresholds that route uncertainty to humans.

LAYER 02

Memory

Short-term context for the task at hand, long-term knowledge of your business, and recall of past interactions.

LAYER 03

Planning

Breaks goals into steps, sequences and parallelises them, and retries or replans when reality disagrees.

DecomposeSequenceRetryReplan
LAYER 04

Tool use

MCP-native access to your systems — queries, transactions, and workflow triggers, all schema-validated and logged.

LAYER 05

Orchestration

Specialist agents hand off, work in parallel, and escalate — coordinated by the runtime, visible in the audit trail.

Agent Types

Five shapes of work

Compose them freely — most production workflows use several together.

Conversational

Customer- and employee-facing dialogue across voice, chat, WhatsApp, and email — context preserved everywhere.

Workflow

Backend automation that runs multi-step processes across systems — no conversation required.

Document

Reads, extracts, validates, and generates — contracts, claims, KYC files, reports.

Decision

Scores, evaluates, and recommends within policy bounds — credit checks, risk flags, routing calls.

Orchestrator

Coordinates the others — delegating, sequencing, and escalating across a team of specialist agents.

agent-runtime · trace
# Goal: resolve billing dispute #5521
plan: 4 steps · 2 tools · 1 approval gate
→ fetch_invoice(#5521) 
→ compare_with_contract() ✓ mismatch found
→ propose_credit($184) — awaiting approval
→ human approved 
→ apply_credit() · notify_customer() 
✓ Resolved · full reasoning trace logged

Autonomy you can watch

Every plan, tool call, and decision is visible in the trace — including the moments where a human weighed in. Autonomy without opacity.

  • Reasoning steps and tool calls fully logged
  • Approval gates exactly where you set them
  • Replay any run, step by step
Build One

From idea to live agent — three steps

STEP 01

Define

Role, knowledge, tools, and guardrails — set declaratively in the studio, no glue code.

Declarative config
STEP 02

Deploy

Validated in a sandbox, secured with scoped permissions, and promoted with rollback ready.

Audit-ready from day one
STEP 03

Run

Multi-step execution in production, across every channel, around the clock — observable throughout.

24/7 · Observable
FAQ

Common questions, answered

It pursues a goal, not a script — decomposing tasks, choosing tools, recovering from failures, and completing work with minimal supervision, inside policies you define.

RPA replays fixed clicks and breaks when screens change. Agents reason over intent and call systems through governed interfaces — they adapt instead of breaking.

Yes — the plan, each tool call, each decision, and each human approval are logged and replayable for every run.

Natively. Orchestrator agents delegate to specialists, run steps in parallel, and merge results — all visible in one trace.

Get Started

Put an agent on your hardest workflow.

We’ll build one against a real process in your first working session.

Book a Demo