AI automation systems

AI that runs inside real workflows — with accountability.

Workflow automation, customer systems, internal tools, assistants, knowledge bases, CRM automation, and data processing — integrated into the tools your teams already use.

AI workflow automationAI customer systemsInternal AI toolsKnowledge & retrievalCRM & ops automationAI data processing

Operational AI: guardrails, logging, and measurable throughput — not science-fair demos.

Operating principles

Production-grade automation — not buzzwords.

We design for accuracy, rollback, and human oversight where stakes are high.

Process map before models

We document inputs, decisions, and failure modes — most value is in the workflow design, not the model name.

Human-in-the-loop by design

Escalations, approvals, and sampling loops where mistakes are expensive.

Grounded knowledge systems

Retrieval over your documents with citations, freshness rules, and access control aligned to RBAC.

Integration-first

CRM, ERP, helpdesk, email, Slack/Teams — automations live where work already happens.

Evaluation & monitoring

Offline tests, live drift checks, and dashboards your ops team can read.

Security-aware defaults

Data minimisation, redaction patterns, and audit logs suitable for internal and customer-facing use.

Use cases

Where minutes saved become margin.

Finance & back office

Documents that no longer need a human opener.

Invoices, contracts, and proofs routed, extracted, classified, and pushed into ERP/finance with validation rules and exception queues.

Outcomes

  • Lower cycle time
  • Fewer posting errors
  • Scales without linear headcount
Customer operations

Consistent answers without a script warehouse.

Assistants grounded in policies and systems of record — with handoff to humans when confidence drops or accounts are sensitive.

Outcomes

  • 24/7 first-line coverage
  • Reduced handle time
  • Auditable responses
RevOps & CRM hygiene

Stop losing pipeline to bad data.

Enrichment, deduplication, routing rules, and AI-assisted updates that respect governance and territory logic.

Outcomes

  • Cleaner pipeline
  • Better forecasting inputs
  • Less manual CRM policing
Capabilities

Examples of AI systems we build.

If your workflow is not listed, we still assess it — these are common entry points.

AI workflow automation
AI customer systems
AI internal tools
AI business assistants
AI knowledge systems
AI operations automation
AI CRM automation
AI-powered approvals & routing
AI data processing & classification
Ticket triage & summarisation
Contract / clause extraction
Multi-system orchestration
Delivery

From pilot to production without drama.

01

Workflow & risk analysis

We quantify error tolerance, latency needs, and where humans must stay in control.

02

Pilot with real data

Shadow mode or sampled production traffic — metrics before mandates.

03

Hardening

Guardrails, monitoring, rate limits, and fallback paths when providers or models change behaviour.

04

Operate & improve

Runbooks, owner training, and iteration cadence tied to business KPIs — not vanity accuracy scores.

Planning ranges

Outcome-scoped engagements.

We price against defined workflows and acceptance tests — not open-ended “AI retainers”.

Focused workflow

From EUR 3,500

One high-friction workflow automated end-to-end with monitoring.

  • Process map
  • Integration to 1–2 systems
  • Evaluation harness
  • 4–6 week slice
Automate one workflow
Most selected

AI system

From EUR 9,500

Assistant, knowledge, or operations hub with RBAC, logging, and admin controls.

  • Security review pass
  • Human-in-the-loop
  • Dashboards
  • 8–12 week programme
Design an AI system

Programme

Custom

Multiple workflows, fine-tuned retrieval, or long-running improvement partnership.

  • Dedicated cadence
  • SLA options
  • Change management support
  • Model/provider flexibility
Plan a programme

Large language models are tools; liability and data handling stay explicit in the contract.

FAQ

AI delivery — plain language.

Do you sell “AI marketing packages”?

No. We engineer AI inside business systems — automation, retrieval, classification, and operations tooling — not generic content churn.

Which models do you use?

The right one for the job — judged on latency, cost, and evaluation scores against your data. We avoid lock-in where possible.

How do you protect data?

Region choices, retention limits, redaction, and access scopes are decided up front — documented alongside the architecture.

What does success look like?

Measured in throughput, error rates, and time returned to teams — not slide decks about innovation.

Which workflow burns the most hours today?

Send a short description — we reply with a feasibility view, risks, and a suggested pilot boundary.

Brief an AI system

Reply within one business day