AI AGENTS
AI agent development services for real workflows
Our AI agent development services build agents that plan multi-step work, call your systems through approved tools and stop for a person when rules or confidence require it. Each one is tested against your own cases first.
AI Jumpstart
- One workflow mapped with tool permissions and limits
- Working agent prototype on your systems in a sandbox
- Scenario eval report with a go, reshape or stop decision
WHY IT MATTERS
An agentic AI development company that plans for failure
An agent is software that decides its own next step. That makes it useful and risky. We define what each agent may do, log every action, cap spending and design the hand-off to a person before we write the first prompt.
CAPABILITIES
What our AI agent development services include
Workflow and tool design
We map the task, choose which systems the agent may call, and define the inputs, outputs and limits for every tool it uses.
LangGraph agent builds
Stateful agents built on LangGraph with retries, checkpoints and branching, so long tasks survive timeouts and resume where they stopped.
Orchestrating several agents
Planner, researcher and reviewer agents that split complex work between them, with clear contracts and tests at every hand-over point.
Approval steps for people
Agents pause for sign-off on payments, customer messages or record changes. Reviewers see the agent's reasoning and evidence before approving.
Agent evaluation suites
Scenario tests that score task completion, tool-call accuracy and policy breaches, run on every change before anything reaches users.
Monitoring and cost control
Traces for every run, alerts on loops or failures, and token budgets per task, so costs stay predictable as usage grows.
USE CASES
Where AI agents save real hours
Invoice matching for manufacturers
An agent matches supplier invoices to purchase orders and goods receipts in your ERP, flags mismatches and drafts queries to suppliers.
Client onboarding at CA practices
The agent collects KYC documents, checks them against a checklist, chases missing items by email and prepares the file for partner review.
Sales research and CRM updates
Before each call, an agent researches the account, summarises recent emails and updates CRM fields, leaving a short brief for the rep.
IT service desk resolution
Password resets, access requests and known fixes run end to end, with anything unusual routed to an engineer along with full context.
HOW WE DELIVER
Five gates. You sign each one.
Every AI Agents engagement runs on PRISM OS. Nothing moves to the next phase until you approve the evidence.
Plan
Choose one workflow, its owner and what the agent may do
You sign: Problem BriefResearch
Map systems, APIs, edge cases and approval rules
You sign: Frozen PRD-LiteImplement
Build the agent in a sandbox with scenario tests
You sign: Working prototype + eval reportStabilise
Add guardrails, budgets, audit logs and human sign-off points
You sign: 3-click UAT sign-offMaintain
Review traces monthly, tune tools and extend to new tasks
You sign: IP handover + warrantyAI Jumpstart
A fixed-scope first step. You keep everything it produces, whether or not you build with us.
- One workflow mapped with tool permissions and limits
- Working agent prototype on your systems in a sandbox
- Scenario eval report with a go, reshape or stop decision
WHY SMARTX
Why SmartX for AI Agents
Narrow scope first
We automate one workflow well before adding more. A focused agent with clear limits earns trust faster than a general one.
Every action is traceable
Each tool call, input and decision is logged, so your auditors and engineers can replay exactly what the agent did and why.
Your systems, your rules
Agents run inside your cloud with scoped credentials. They can only touch the systems and records you approve in writing.
One team, start to finish
The engineers who prototype your agent lead the production build, so design decisions and edge cases carry straight through to launch.
TOOLS WE USE
The stack, chosen per problem
ENGAGEMENT MODELS
Choose how we work together
Every model keeps the same signed gates, fixed milestones and full code ownership.
Gated delivery pod
A senior pod owns the outcome from Problem Brief to production, priced per gate so you can stop at any signature.
Dedicated engineers
Engineers who join your team and sprints, with PRISM briefs and evidence reviews added on top of your process.
PRISM OPS retainer
Hosting, security and a monthly improvement budget, run by the same engineers who built the system.
SELECTED WORK
Evidence, not promises.
Business workflow automation for a rapid construction business
We documented how work really flowed, worked through the unclear cases with the team and automated the process at pace.
Now growing through deeper customer engagement.
Read the case study“SmartX is our technology partner for business workflow automation of our rapid construction business. We found the SmartX team to be extremely diligent and thorough in working through ambiguous situations, documenting the process flows and implementing the solution at a fast pace.”
FAQ
Questions before you book
Not covered here? Ask on the call.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions. An agent takes actions: it plans steps, calls tools such as your CRM or ERP, checks the results and keeps going until the task is done or a person needs to decide.
How do you stop agents making costly mistakes?
We scope tools tightly, require approval for sensitive actions and keep a human in the loop wherever errors are expensive. Scenario tests run before every release, and spending budgets stop runaway loops before they cost you anything.
Can you handle simpler automation as well?
Yes. Our AI automation services cover rule-based flows too, as in the business workflows we automated for UBC Impex. If a step needs no judgement, we use plain code or a workflow tool, which is cheaper to run and easier to test than an agent.
Which frameworks do you build agents with?
Mostly LangGraph for stateful agents, plus the OpenAI Agents SDK or Model Context Protocol where they fit. We choose the model per task and keep it swappable as prices and capabilities change.
When do you split work across several agents?
Only when one agent cannot hold the whole task, such as research followed by independent review. Multi-agent systems add cost and failure points, so we start with one agent and split only when tests show a clear gain.
START WITH CLARITY
Pick one workflow for your first agent
Book a free discovery call and we will help you choose a workflow where an agent saves time without adding risk.
- 1We review your context within one business day.
- 2A senior product engineer joins the call.
- 3You leave with a clear recommended next step.