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We spent years automating finance, procurement, logistics and marketplace operations, and measuring every result. That process knowledge is what makes AI agents safe and useful in production. Today we build with AI development harnesses, taking a business problem to a measured outcome in 8 weeks.
What changed
Process expertise
Broader scope
Each of these builds on a problem we've already solved.
Invoices, bills of lading, shipping documents and buyer orders read and checked without per-template setup.
Built on: 95%+ less effort
Price variances, missing data and mismatches resolved against your rules and history, with people looped in only when needed.
Built on: 1M+ SKUs
Direct links between ERPs, sourcing platforms, banks and marketplaces, including systems with no ready-made connector.
Built on: 90% faster
Exception queues and approval steps shaped to how your team works, with the evidence already gathered.
Built on: under 2 minutes
Employees ask, report and update by chat or voice, and the right system updates itself.
Built on: our AI helpdesk assistant
Computer-use agents take over where screen bots used to break.
Built on: 45% → 98% compliance
The 8-week path
One fixed window, agreed up front. Supplier invoice processing for Al Dahra went live in six weeks.
We sit with the people doing the work, baseline the hours, errors and cycle time, and agree the one number we'll move.
AI development harnesses let us build agents, integrations and tools fast, connected to your ERP, portals and inboxes. Exceptions and controls are designed in from the start.
It runs alongside your team on real volumes until the results match, then takes over the routine. Your people handle only the exceptions.
We measure against the week-one baseline and hand over, with ongoing support as your volumes and processes change.
Questions
It's an engineering setup where AI models write, test and revise code alongside our engineers, inside guardrails we control. It lets a small team build agents, integrations and internal tools in the time a single rule-based automation used to take.
Agents are good at reading messy inputs and making judgment calls. In production, though, they fail on controls, reconciliations and edge cases. Years of automating these exact processes taught us where those edge cases are, so we design for them from day one.
The same way we kept automations safe: fail-safes on every match, approvals wherever money or master data changes, an audit trail on every action, and reconciliation back to your system of record. Our shipping document validation for Al Dahra runs with 0% false positives.
No. Every one of our 23 case studies was built around existing systems, including Sage, SAP Ariba, Amazon Seller Central and Walmart.
Yes, for stable, high-volume, rule-based steps. We now use it as one component inside agentic solutions, not as the whole answer.
Everything from defining the problem and agreeing the KPI in week one to measuring it in week eight. The solution is designed, built, run live alongside your team and handed over inside that window.
You keep ongoing support from our team as your volumes and processes change. Many clients then move to their next process: Al Dahra now runs 14.
Yes. We deliver in India and internationally, including for Al Dahra's global operations and a procurement transformation for a billion-dollar logistics company in the Middle East.
Bring one process. In 30 minutes we'll tell you whether it's worth automating, which KPI we'd move and how we'd get there in 8 weeks.