Agentic Workflows & Orchestration

Multi-agent systems that carry a process end-to-end — planning, acting, verifying, and escalating like a well-run team.

We design and run agent meshes for processes that span many systems: orchestration with state, retries, and audit trails; retrieval grounding so agents act on your data; and verification gates so nothing ships unchecked. We operate production multi-agent platforms ourselves — this is engineering we live with, not a slide.

How it works: inbound work goes to a planner agent, worker agents execute, a verification gate checks every output, humans decide the edge cases, and your systems receive the result — with a full audit trail underneath.

• A process owned end-to-end instead of handed between queues
• Fewer handoffs, fewer dropped edge cases, fewer errors
• Every agent decision logged, auditable, and reversible

What this usually includes

• Agent-mesh and workflow design around your systems
• Orchestration layer: state, queues, retries, and escalation paths
• Retrieval grounding and verification gates on agent output
• Monitoring, audit trails, and human-checkpoint design

Best fit for

• Processes that cross several systems and teams
• Operations that need 24/7 execution with accountability
• Teams already using single automations that hit their limits

A delivery approach grounded in operations, not hype

1. Map the process, its systems, and its failure modes
2. Design agent roles, checkpoints, and escalation rules
3. Deploy, observe live behaviour, and tune for reliability

What we can build for you

• A claims mesh that reads the loss notice, chases missing documents, checks cover and drafts the settlement, with an adjuster signing off before anything is paid
• When a shipment runs late, the exception crew spots it, rebooks the carrier, updates your TMS and warns the customer before they ring you
• Referral intake for clinics: eligibility verified, prior records gathered, the appointment booked, and incomplete files handed to your staff, not guessed at
• One agent extracts contract clauses, a second checks them against your playbook, a third routes the exceptions to counsel
• Out of hours, an incident team triages helpdesk alerts, applies the fixes it already knows, logs every step it takes, and wakes an engineer only when it is genuinely stuck
• A supplier-quality loop that logs defects, raises NCRs in your ERP, chases 8D responses and checks the corrective action actually landed
• The returns crew authorises the RMA, books the courier, grades the inspection photos and releases the refund once stock scans back in
• For local authorities, a permit chain validates applications, requests missing evidence, checks planning rules and queues each decision for officer sign-off
• KYC refresh, run by a single agent: registry extracts pulled, sanctions lists screened, the file assembled for compliance approval
• A procure-to-pay mesh matches purchase orders, receipts and invoices across ERP and inbox, and parks every mismatch for a human to rule on

Frequently asked questions

What happens when an agent gets it wrong?

Nothing ships unchecked. Every output passes a verification gate that compares it with your source data, and anything ambiguous escalates to a named person with the full context attached. New agents start in shadow mode, proposing actions rather than taking them; they get write access once their log has earned your trust. Escalation to a human is part of the design, not a failure state.

How much integration work lands on our IT team?

Less than you might fear. We build around the CRM, ERP and helpdesk you already run, connecting through their APIs, so nothing gets ripped out and there is no per-seat licensing. From your side we need API credentials, a sandbox and a regular hour with whoever owns the process. The honest caveat: where a core system has no usable API, that part takes longer, and we will tell you during design, not halfway through the build.

Where does our data go, and which AI models see it?

Your data stays on EU-hosted infrastructure, and GDPR shapes the build from the first design session rather than being bolted on later. We are LLM-agnostic, so we pick models per task and per sensitivity level. Because agents fetch records from your systems at run time, your database never gets copied into anyone's model. Every read, write and decision lands in an audit trail you can inspect.

We already run workflow automations. When is an agent mesh the wrong answer?

When a flowchart already covers it. If every branch of your process is known in advance and no step needs judgement, keep the automation you have; a mesh would add cost and moving parts for nothing, and we will say so on the first call. Orchestration earns its keep when work crosses several systems, branches on judgement, and has to recover from failures without someone restarting it by hand. Most teams find us after one automation has hit exactly that wall.

Explore the connected parts of the offer

• AI Automations — Use AI where it improves throughput, quality, and decision support.
• AI Integration — AI added to the software and systems you already run — not another tool on the side.
• Business Automation Solutions — Practical automation built around the way your business already works.

Discuss this service: [email protected]