A2 — AI Apps & Integration
Workflow Automation & AI Agents
AI agents that handle multi-step business processes, from lead qualification to invoice reconciliation, with human checkpoints.
Overview
AI agents can take over multi-step work that simple automations can't, such as reading an email, checking a system and deciding what to do next. Without guardrails, they can also take the wrong action confidently.
We design agents with clear boundaries, human approval for important steps, full logging and tested failure paths, so they save time without creating new risks.
What we do
- 01
Map the process and decide what the agent may do
- 02
Connect the agent to your tools and data
- 03
Add guardrails and human approval steps
- 04
Test failure paths and messy inputs
- 05
Monitor and log every action
How we work
- Step 1
Discover
We agree the use case, data sources and what a good answer looks like.
- Step 2
Build
We integrate the model, your data and your product in short iterations.
- Step 3
Evaluate
QA tests accuracy, safety and edge cases against an evaluation set before launch.
- Step 4
Monitor
We track quality and cost in production and keep improving.
Who it's for
- Operations teams buried in repetitive multi-step work
- Sales teams qualifying large volumes of leads
- Finance teams matching and reconciling documents
What you get
- A process map with automation boundaries
- A working agent connected to your tools
- Guardrails, approvals and logging
- Failure-path tests and monitoring
Questions
Will the agent act without anyone checking?+
Only where you're comfortable. Important or irreversible actions go through human approval.
What if the agent makes a mistake?+
Every action is logged, risky steps need approval, and we test failure cases before launch so mistakes are caught and reversible.
How quickly can you start?+
Most engagements start within 5–7 business days of agreeing scope, and urgent work can start within 48 hours.
Tools
- n8n
- Zapier
- LangChain
- OpenAI
- Claude
- AWS Bedrock
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