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Intelligence

AI Agent Development & Intelligent Automation Services

An agent is only trustworthy when every action it can take is defined, permissioned, logged and reversible.

Autonomous Agent Task Runner
Execution Trace: 180ms
STEP 1Tool: CRM & Lead IngestionOK ✓
STEP 2Agent: Context Enrichment & ScoringOK ✓
STEP 3Approval Gate: Send Contract
ApproveReview
🛡️ Bounded Execution & Token Budget$0.003 Cost / Run

Overview

Where this fits

Automation stops being useful when the exception rate rises. Agents help because they can interpret unstructured input and choose between defined tools — within limits you set.

We build agents with explicit tool contracts, human approval gates on consequential steps, and a complete trace of every decision.

What we build

Delivery within ai agents & automation

Task agents

Bounded agents that triage, enrich, route and complete repetitive work.

Workflow automation

Event-driven pipelines across email, documents, CRM and internal systems.

Human-in-the-loop reviews

Queues where a person approves, edits or rejects before anything commits.

Agent observability

Traces, cost per run, success rates and failure replay.

Problems we solve

What usually brings clients here

  • 01Teams spending hours on copy-paste between systems.
  • 02Rule-based automation that breaks on every unusual case.
  • 03No audit trail for automated decisions.
  • 04Runaway automation with no cost or rate control.

Key capabilities

What is included

  • Tool and function definition
  • Planning and multi-step execution
  • Approval gates and escalation
  • Retries, timeouts and idempotency
  • Run tracing and replay
  • Cost and rate governance

Agents

Tool-calling LLMs, orchestration frameworks, state machines

Runtime

Queues, durable workflows, scheduled jobs

Control

Permissions, approval queues, kill switches

Insight

Run traces, evaluation, cost dashboards

Use cases

Where it makes the biggest difference

Inbox triage

Classifying inbound requests, extracting details and creating structured records.

Order and claim processing

Validating, matching and progressing cases with exceptions escalated.

Research and enrichment

Gathering and structuring information into a reviewed dataset.

Our approach

How the engagement runs

  1. 01

    Scope

    Pick one high-volume process and define done, safe and out-of-bounds.

  2. 02

    Instrument

    Expose the systems involved as clean, permissioned tools.

  3. 03

    Pilot

    Run in shadow or approval mode and measure against the human baseline.

  4. 04

    Widen

    Expand autonomy only where the metrics justify it.

FAQs

Questions we are asked

Will an agent act without oversight?

Only where you decide it should. Consequential actions default to an approval step until metrics justify autonomy.

What if it makes a mistake?

Actions are logged, reversible where possible, and every run can be replayed to find the cause.

How do you control cost?

Per-run budgets, model routing, caching and dashboards that attribute spend to each workflow.

Planning ai agents & automation?

Let's scope it properly.

Tell us the problem, the constraints and the deadline. We will come back with an approach, not a brochure.