Field notes on AI workshops, automation and integration
Every bullet on our services cards has a longer write-up here: what it is, how we do it, where it fails, and what to check before you start. 13 articles, no incense.
Workshops
How we turn "AI ideas" into a scored shortlist, a data-readiness check, an architecture sketch and a 30/60/90-day plan.
AI use-case shortlist and scoring: from a pile of ideas to a ranked plan
A scoring model (value, feasibility, data, risk, time-to-impact) that turns a pile of AI ideas into a buildable shortlist, plus what a bad shortlist looks like.
Workshops / Data readiness + constraintsAI data readiness: is the data there, accessible, clean and legal to use?
A scorecard for the data of an AI use case: does it exist, can you reach it, is it clean enough, may you use it, and what GDPR, access and latency limits apply.
Workshops / Architecture sketchThe AI architecture sketch: one page that beats a 40-page design document
The one-page AI architecture sketch: triggers, n8n workflows, LLM calls, vector search, systems of record, approval steps and where the guardrails sit.
Workshops / 30/60/90-day roadmapThe 30/60/90-day AI roadmap: one automation live, then measure, then expand
A 30/60/90-day AI roadmap: one automation live by day 30, measurement and a second use case by 60, operate and expand by 90, with owners and kill criteria.
Automations
Resilient n8n workflows for the unglamorous work: lead routing, support triage, reporting, back-office operations.
Lead routing and enrichment: automating inbound leads with n8n and LLMs
Automate inbound lead handling with n8n and LLMs: enrichment, intent and urgency scoring, routing rules, SLA timers, CRM updates and failure modes to plan for.
Automations / Support triage + taggingSupport triage and tagging: LLM ticket classification with a human in the loop
Classify support tickets by intent, urgency, product area and sentiment, draft replies for human review, keep tag taxonomies stable and measure triage accuracy.
Automations / Reporting + dashboardsAutomated reporting and dashboards: pipelines that replace the weekly report
Replace hand-built weekly reports with an n8n pipeline from Postgres, Sheets and CRM to dashboards and chat. Numbers come from queries, narrative from an LLM.
Automations / Back-office ops automationBack-office ops automation: resilient workflows that replace repetitive admin
Automate back-office work — invoicing nudges, document handling, onboarding, approvals, data sync — with retries, idempotency, logging and clean ownership.
AI Integration
Shipping AI inside real products and tools: integration, evaluation, guardrails, red-teaming, deployment and monitoring.
API and UI integration: embedding AI in an existing product or internal tool
Embedding an LLM in an existing product: API design (structured outputs, timeouts, streaming), UI patterns that earn trust, and the two mistakes to avoid.
AI Integration / Evaluation harnessEvaluation harness: proving an LLM feature still works after each prompt change
How to build an evaluation harness for an LLM feature: a reference set from real cases, per-task metrics, and regression gates on every prompt or model change.
AI Integration / GuardrailsAI guardrails: runtime limits that keep a wrong model output from becoming an incident
AI guardrails explained: six runtime layers (input, output, action limits, approval gates, uncertainty, prompt injection) for workflows that touch money.
AI Integration / red-teamingRed-teaming an AI workflow: attack your own system before someone else does
Red-teaming playbook for LLM automations: prompt injection in documents, bank-account swaps, malformed files, edge cases — and the guardrail that closes each.
AI Integration / Deployment + monitoringAI deployment and monitoring: staging, canary, and the metrics that matter
Taking an AI workflow to production: staging, canary, full rollout, pinned model versions, cost and latency budgets, and the monitoring that catches drift.
Describe the workflow, the pain and the tools you use. We reply with next steps and a proposed approach — no deck, no incense.