AI Agent Development
Autonomous Agents That Actually Work in Production
We build intelligent AI agents for real business workflows — from inventory automation and dynamic pricing to customer support and B2B negotiation — engineered for reliability, not demos.
80%
Reduction in Manual Tasks
24/7
Agent Uptime
6 Wks
Agent POC Delivery
3×
Faster Workflow Execution
Autonomous AI Agents That Execute Real Business Workflows — Not Just Chat
Most AI implementations stop at generating text. AI agents go further: they plan, decide, call tools, take actions, and complete multi-step workflows autonomously — from processing invoices and triaging support tickets to executing trades and managing inventory reorders without human intervention.
We build production-grade AI agents grounded in your business data, integrated with your existing systems, and designed with explicit guardrails and observability. Every agent we deploy is auditable — you can trace every decision, every tool call, and every action taken, making it safe to deploy in regulated and mission-critical environments.
Whether you need a single task-specific agent or a coordinated multi-agent system handling complex enterprise workflows, we engineer for production reliability: error recovery, escalation paths, logging, and human-in-the-loop review at every critical decision gate.
- Multi-step autonomous execution — not just chatbots, but workflow agents that take action
- Full auditability and traceability — every decision logged and explainable
- Tool-use and system integration — CRM, ERP, databases, APIs, and external services
- Human-in-the-loop escalation paths built into every high-risk decision gate
80%
Reduction in Manual Tasks
AI Agent Development Capabilities
A complete suite — from initial workflow mapping through to production deployment and ongoing optimisation.
Inventory & Procurement Agents
Automated PO generation, supplier negotiation, and reorder triggering based on real-time demand signals.
Dynamic Pricing Agents
Competitor monitoring and demand-based price adjustment within predefined margin boundaries.
Profitability Analysis Agents
SKU-level margin analysis with bundling and clearance recommendations to optimise product portfolio.
Customer Support Agents
Intent-aware support agents that resolve queries, escalate to humans intelligently, and learn from interactions.
Data Pipeline Agents
Autonomous agents that extract, transform, and load data across systems with validation and error recovery.
B2B Negotiation Agents
Email and chat-based negotiation agents operating within margin rules to close deals faster.
Content Optimisation Agents
Detect ranking declines, refresh product content, and run automated A/B tests on copy and layout.
Use Cases in Production
Real deployment patterns — the specifics vary per client, but the structure stays the same.
E-commerceAutonomous Inventory & Replenishment Agent for a Multi-Brand Retailer
A multi-brand e-commerce retailer was managing replenishment across 12,000 SKUs manually — procurement analysts spending 60% of their time on routine reorder decisions using spreadsheet-based safety stock calculations that frequently led to stockouts on fast movers and overstock on slow ones.
An AI replenishment agent integrated with Shopify, their 3PL WMS, and supplier APIs. The agent monitors sell-through velocity, lead times, and seasonal signals in real time, autonomously raises purchase orders below a defined value threshold, and routes larger orders to the procurement analyst with a recommendation pre-populated. Integrated with Slack for alerts and approvals.
- Stockout rate reduced from 8.3% to 1.1% across all SKUs within 90 days
- Procurement analyst reorder time reduced from 60% to 15% of working week
- £340K overstock reduction in 6 months from improved demand signal accuracy
Financial ServicesAI Due Diligence Agent for a Corporate Finance Advisory Firm
A mid-market M&A advisory firm was spending 40 hours per deal on initial due diligence document review — junior analysts reading through hundreds of pages of contracts, financial statements, and regulatory filings to extract key risk flags. The process was slow, expensive, and occasionally missed material issues buried in dense legal language.
A multi-agent due diligence system: a document parsing agent extracts structured data from uploaded deal documents; a risk identification agent cross-references extracted data against a firm-maintained risk taxonomy; a report generation agent drafts a structured due diligence summary with flagged items and supporting evidence references. All findings are traceable to source document and page.
- Initial due diligence review time reduced from 40 hours to 6 hours per deal
- Zero material risk flags missed in 18 months post-deployment — validated by senior partner review
- Capacity for concurrent deal analysis doubled without headcount increase
Customer SupportTier-1 Support Resolution Agent for a SaaS Platform
A B2B SaaS company with 4,000 customers was handling 2,200 support tickets per month, 68% of which were routine queries — password resets, billing questions, feature how-tos, and integration troubleshooting that consumed senior support engineers who should have been focused on complex technical issues.
A support agent integrated with Zendesk, their product knowledge base, billing system (Stripe), and user database. The agent handles routine queries autonomously — resetting passwords, issuing refunds below a threshold, pulling account status, and walking users through documented troubleshooting flows. Complex tickets are escalated to human agents with a structured summary, relevant context, and recommended resolution approach.
- 68% of Tier-1 tickets resolved autonomously — within 90 seconds average response time
- Human support engineers freed to focus exclusively on Tier-2 and Tier-3 issues
- Customer satisfaction score increased from 7.4 to 9.1 / 10 — driven by response speed
Why Choose Us for AI Agent Development
Workflow-First Design
We map your actual business processes before writing code — agents solve real problems, not generic use cases.
Production-Grade Reliability
Built with failover logic, human escalation paths, and monitoring from day one — not retrofitted later.
Measurable ROI
Every agent is instrumented with business-relevant metrics so you can see the impact on revenue and cost.
Deep System Integration
Agents connect to your ERP, CRM, e-commerce platform, and databases via API — no data stays siloed.
Our Delivery Process
A structured path from business process discovery through to live deployment and continuous improvement.
Workflow Mapping
Map the actual business process — inputs, decisions, outputs, edge cases, and escalation paths — before any build.
POC & Validation
Build a focused proof-of-concept in 4–6 weeks to validate agent behaviour under real-world conditions.
Production Development
Full agent build with integration, failover logic, monitoring, and human-in-the-loop escalation where needed.
Deploy & Iterate
Production deployment with performance dashboards, retraining pipelines, and ongoing optimisation.
Industries We Serve
Technologies We Use
Industry-proven tools chosen for performance, reliability, and long-term support.
OpenAI
Python
AWS
DockerFrequently Asked Questions
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