Workflow Automation
Finding the high-friction, repetitive processes draining your team's hours and replacing them with automation that holds up under real volume.
Who this is for
Teams with obvious manual work — data entry, handoffs between systems, repetitive reporting, intake processes — and no clear path to automating it. You know the hours are being wasted. You're not sure what to automate first, what tool to use, or whether the automation will actually hold up once it's built.
The right question before automating anything: Is this process stable enough and high-volume enough to justify automation? We start with discovery, not build. A lot of automation projects fail because they automate a broken process — you get a faster broken process.
How we approach it
Process discovery
We map the process in detail: every step, every system, every handoff, every place where errors occur or time gets lost. We interview the people who actually do the work — not just the manager who describes it. The map is almost always different from what leadership thinks the process is.
ROI prioritization
We score automation candidates by: hours spent per week, error rate, volume growth trajectory, and implementation complexity. We build the business case before recommending anything. If automation won't deliver clear ROI within 6 months, we'll tell you.
Tool selection
The right tool depends on your existing stack, your technical capacity, and your volume. We evaluate options (native integrations, Zapier, Make, custom code) against your actual requirements — not what the vendor recommended.
Build and test
We manage the build — either doing it ourselves or managing a specialist. We design a test harness using historical data before anything goes live. Edge cases that aren't caught in testing become production incidents.
Rollout and documentation
Training for anyone who touches the process, a runbook for your ops team, and 3-4 weeks of monitoring post-launch. Automation that nobody understands breaks the first time something unexpected happens.
What you get
- Process map and ROI analysis
- Tool recommendation with rationale
- Built and tested automation
- Edge case documentation
- Training and runbook
- Post-launch monitoring
AI Readiness Checklist
12 questions that reveal exactly where your team stands — and what to address before your first AI initiative.
Common questions
What kinds of workflows do you automate?
Our focus is on high-frequency, rule-based processes: CRM data entry and enrichment, reporting and dashboard population, document routing and approvals, customer communication sequences, and cross-system data syncs. We prioritize workflows where a mistake has low stakes and the time savings are high and immediately measurable.
How do you decide which processes to automate first?
We run a discovery session to map your workflows, then score each one on four criteria: frequency (how often it runs), time cost (how long it takes), error rate (how often humans make mistakes doing it manually), and integration feasibility. The highest-scoring workflows become Phase 1.
What tools do you use for automation?
We're platform-agnostic and choose tools based on your existing stack. Common choices include Make (formerly Integromat), Zapier, and n8n for orchestration; OpenAI and Anthropic APIs for AI-powered steps; and native integrations in HubSpot, Salesforce, or Zoho where available. We avoid lock-in by documenting every workflow in plain language.
How do you measure ROI from automation?
We establish a baseline before starting — how many minutes per instance, how many instances per week, who's doing it — and we track the same numbers 30 and 60 days after launch. Most clients see 10–25 hours per week reclaimed in Phase 1. We put those numbers in a written summary you can share with leadership.
Ready to get started?
Tell us what you're working on. We'll get back to you with whether — and how — we can help.
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