Data & AI
AI Agent Development
We build custom AI agents on Claude and OpenAI that don't just respond — they reason through a task, call the tools and APIs they need, check their own output, and complete multi-step work with a clear human checkpoint where it counts. Not a chatbot wearing an "agent" label — a system that actually finishes the job.
What We Build
AI Agent Capabilities
Purpose-built agents on the model — Claude or OpenAI — that fits your task, not a one-size-fits-all wrapper.
Task-Specific AI Agents
Agents built for one job — triaging support tickets, qualifying leads, processing orders, generating reports — that plan the steps and execute them, not just suggest what to do next.
Multi-Agent Systems
Coordinated teams of specialised agents handing work between each other — a research agent feeding a drafting agent feeding a review agent — for tasks too complex for a single agent.
Tool & API Integration
Agents connected to your actual systems — CRM, email, calendar, databases, internal APIs — so they can look things up and take real action, not just describe what should happen.
Memory & Context Management
Agents that remember relevant history across a conversation or a long-running task, without losing accuracy or blowing through context limits.
Guardrails & Human Oversight
Clear escalation rules for what the agent can decide alone versus what needs a human sign-off — built in from day one, not bolted on after an incident.
Agent Deployment & Monitoring
Production deployment with full visibility into what the agent did and why — logs, run traces, and usage dashboards so it's never a black box.
How We Work
Our AI Agent Development Process
From defining exactly what the agent should and shouldn't do, to a monitored agent running in production.
Task & Boundary Definition
Defining precisely what the agent is responsible for, what tools it can use, and where its authority ends.
Model & Architecture Selection
Choosing Claude, OpenAI, or a multi-agent setup based on the task's complexity, cost sensitivity, and tool requirements.
Tool & System Integration
Connecting the agent to the real APIs, databases, and internal tools it needs to actually complete the work.
Prompt & Reasoning Design
Designing how the agent reasons through a task step by step, including how it handles ambiguous or incomplete information.
Testing Against Real Scenarios
Running the agent against real historical cases and adversarial edge cases before any live data or customer touches it.
Launch & Ongoing Tuning
Going live with monitoring in place, then refining the agent's behaviour based on real-world run logs.
Why SharpLogic
Why organisations choose us for AI agents
Agents that finish the task
We build for task completion, not just fluent conversation — the agent takes the action, not just describes it.
Built-in human checkpoints
Every agent has a clear, deliberate answer for when it hands off to a person — never a silent guess on something that matters.
Claude and OpenAI, whichever fits
We're not locked into one model vendor — we pick the model and architecture that fits your task and budget.
Full visibility, no black box
You get real logs of every decision and action the agent takes — auditable, explainable, and easy to hand to compliance.
Industries We Serve
AI agents across every sector
Agents that get things done
Ready to build your AI agent?
Tell us the task that keeps eating your team's time — we'll tell you honestly whether an agent is the right fix.