AI automation systems

Accountable AI for real workflows.

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

We build operational AI with guardrails, logging and measurable throughput, not experimental 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 from start to finish, 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