AI Workflow Automation

We build AI-augmented workflows that connect your existing tools, draft outputs with LLMs, and route the important stuff to people for approval. Less ticket-shuffling, faster cycle times, fewer manual mistakes.

AI Workflow Automation

Automate the boring parts — keep humans where they matter.

Reliable workflow automations with LLM steps where they add value, deterministic logic everywhere else, and proper observability.

Common signs your team is overdue for ai workflow automation:

  • Teams copying data between CRM, email, spreadsheets, and Slack all day
  • High-volume, low-judgment tasks eating headcount (lead routing, document tagging, status updates)
  • Drafts that should take seconds (replies, summaries, briefs) take hours
  • Existing Zapier/Make flows breaking silently — no observability, no tests

What we build for ai workflow automation:

  • n8n / Make / Zapier orchestration — self-hosted when needed
  • LLM nodes for drafting, classification, extraction, summarization
  • Human-in-the-loop approvals via Slack, Teams, or email
  • Failure handling, retries, idempotency, and audit logs
  • Cost dashboards and alerts so spend can’t surprise you
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Capabilities

Where it pays off fastest

Reliable, observable automations — outcomes our clients keep coming back for.

  1. Inbox triage

    Classify, summarize, and draft replies for shared inboxes — humans approve before send.

  2. Invoice & document handling

    Extract structured data from PDFs, route exceptions, post into your accounting system.

  3. Lead enrichment & routing

    Enrich inbound leads, score them, assign to the right rep with a personalized follow-up draft.

  4. Support deflection

    Auto-draft replies grounded in your help center; escalate edge cases with full context attached.

How we deliver · Discovery → ship in 4 weeks
  1. Map the workWatch the actual process. Identify the 20% of steps causing 80% of the toil.
  2. Design with guardrailsDecide what AI drafts vs. what AI decides. Define HITL checkpoints.
  3. Build & dogfoodShip one workflow end-to-end. Real users, real data, week two.
  4. Roll outAdd the next workflow. Train the team. Hand over runbooks.
Tools & platforms we use
n8nMakeZapierOpenAIAnthropicSlackMicrosoft 365HubSpotSalesforceAirtablePostgresLangfuse
Talk to an engineerFree 30-minute consultation
FAQ

Questions teams ask us about AI Workflow Automation

Still unsure? Talk to an engineer. It’s free and there are no slides.

Ask us anything
Should we use n8n, Make, or Zapier?
Depends on volume, data sensitivity, and team. Zapier for the simplest cases; Make for richer flows; n8n (often self-hosted) when you need full control or have data residency rules. We’ll recommend in discovery.
How long does it take to get to production?
Most projects ship a real, usable system in 3–6 weeks. Discovery is 1–2 weeks; build sprints are weekly with demos.
Will my data be used to train models?
No. We default to enterprise tiers (OpenAI, Anthropic, Bedrock, Vertex) that don’t train on your data. For sensitive use cases, we deploy open-weight models on your infrastructure.
How do you control costs?
We design cost-aware from day one — model routing (cheap model first, escalate when needed), caching, batch processing, and per-user budgets with alerts.
Can you work with our existing engineering team?
Yes. We embed alongside your team, transfer ownership progressively, and document everything we build.
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Let's build something amazing together.

Our deep pool of certified engineers and IT staff are ready to help you to keep your IT business safe & ensure high availability.

  1. 1
    Tell us about your projectA few lines is enough to get started.
  2. 2
    A 30-minute callWe listen, ask the right questions and scope it.
  3. 3
    A sharp, honest planClear next steps and a quote. No obligation.

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