Document Processing & Extraction
Invoices, contracts, applications, medical records, compliance documents — AI reads, extracts, validates, and routes them. No more manual data entry. No more missed fields.
Intelligent Automation
Your team is too good for the work
Your team is too good for the work
that's eating their day.
Every business has processes that should run themselves — document intake, data extraction, compliance routing, report generation, customer onboarding. Intelligent Automation makes them run faster, more accurately, and without burning your best people on work a system should handle.
—— What we automate
The work your team does every day — that a system should be doing instead.
Workflow Orchestration
Multi-step approval chains, handoff sequences, escalation rules, and routing logic — automated end to end with human-in-the-loop where it matters.
Data Pipeline Automation
Pulling data from disparate systems, cleaning it, transforming it, and delivering it where it needs to go — on schedule, every time, without someone babysitting a spreadsheet.
Report Generation & Distribution
Weekly reports, compliance summaries, client updates, board decks — generated from live data and delivered automatically to the right people at the right time.
Customer Operations
Onboarding flows, account setup, verification checks, renewal processing — the operational backbone of customer experience, automated without losing the human touch.
Compliance & Quality Checks
Automated validation against regulatory requirements, internal standards, and business rules — catching errors before they become problems.
—— Why now
What becomes possible when the manual work disappears.
Your team works on what matters
The analyst who spends three hours a day copying data between systems? That's three hours of strategic work you're not getting. Automation gives it back.
Errors drop to near zero
Manual processes have manual error rates. Automated workflows run the same way every time — validated, logged, and auditable.
You scale without scaling headcount
When a process runs itself, doubling volume doesn't mean doubling the team. Growth becomes a software problem, not a hiring problem.
You can actually measure it
Every automation we build ships with dashboards: hours saved, throughput, error rates, cost per transaction. You'll know exactly what it's worth — and so will your board.
—— How it works
From workflow mapping to live automation.
Every engagement starts with understanding how the work actually gets done today — not how the org chart says it should.
1
Discover
Workflow Discovery
We map the actual process — not the documented process, the real one. Who touches what, where the bottlenecks live, what the error rates look like, and where automation will have the highest impact.
2
Design
Design & Architecture
Design the automated workflow with the right balance of AI and human oversight. Define triggers, decision points, exception handling, and the handoff points where a person still needs to be in the loop.
3
Build
Build & Integrate
Build the automation, integrate it with your existing systems — ERP, CRM, document management, email, Slack — and test it against real data.
4
Launch
Deploy & Measure
Deploy to production with monitoring, alerting, and dashboards. Run parallel with the manual process until confidence is established. First performance report within two weeks of go-live.
—— The build, week by week
An automation build, plotted out.
A typical mid-complexity engagement. Phases overlap — design continues while the first integrations are being built.
DISCOVER
DESIGN
BUILD
LAUNCH
WEEK 1Week 1
WEEK 2Week 2
WEEK 3Week 3
WEEK 4Week 4
WEEK 5Week 5
WEEK 6Week 6
WEEK 7Week 7
WEEK 8Week 8
—— Investment
What it costs to stop doing it by hand.
Scoped to the number of workflows and the complexity of your systems.
Scoped to your needs
Contact for pricing
Engagements scoped individually based on workflow complexity, number of systems, and integration requirements.
Start a conversation →- Workflow discovery and process documentation
- Automated workflow — built, tested, deployed
- Integration with your existing systems
- Human-in-the-loop decision points where appropriate
- Monitoring, alerting, and error handling
- Performance dashboard — hours saved, error rates, throughput
- Documentation and runbooks for your team
- All source code and configuration — yours
—— Selected work
Products we've shipped that run in production.
A few of the products we've built and shipped — the same engineering discipline we bring to every automation we put in production.
—— Where automation leads
Every automation we build connects to what comes next.
Intelligent Automation is powerful on its own — and even more powerful as part of a full engagement.
AI Audit
Identify which processes across your organization have the highest automation potential.
Explore the AI Audit →AI Prototype Sprint
Validate the automation concept before committing to a full build.
Explore the Prototype Sprint →AI-Native Development
When the automation need is actually a new product.
Explore AI-Native Development →AI Agentic Systems
When the workflow needs judgment and decision-making, not just execution.
Explore AI Agentic Systems →AI Growth Engine
Instrument and optimize automations after launch.
Explore the AI Growth Engine →—— Common questions
What teams ask first.
Automation vs. agents, system integrations, exception handling, measuring ROI, and where to start.
How is Intelligent Automation different from AI Agentic Systems?
Intelligent Automation targets defined, repeatable processes where the goal is throughput, accuracy, and consistency — think document processing, data pipelines, and compliance checks. Agentic systems are for workflows that require judgment, decision-making, and the ability to adapt to novel situations. If the process follows predictable rules, automation. If it requires reasoning and action in unpredictable contexts, agents.
What systems can you integrate with?
Most enterprise systems — CRMs (Salesforce, HubSpot), ERPs (SAP, NetSuite, Oracle), document management platforms (SharePoint, Google Drive, Box), communication tools (Slack, Teams, email), databases, and custom internal tools via APIs. If your system has an API or supports file-based integration, we can connect to it.
How do you handle exceptions and edge cases?
Every automation includes exception-handling logic and human-in-the-loop escalation paths. When the system encounters something outside its defined boundaries — an unusual document format, a data anomaly, a failed validation — it routes to a person with full context. Over time, we analyze exception patterns and expand the automation to handle recurring edge cases.
How do you measure ROI?
Every automation ships with a performance dashboard that tracks hours saved, throughput (items processed per day/week), error rates, cost per transaction, and exception frequency. Your first performance report lands within two weeks of go-live, and the dashboard updates in real time. You'll know exactly what the automation is worth.
Can we start with one workflow and expand later?
That's the approach we recommend. Start with the workflow that has the clearest ROI — usually the one that's most manual, most error-prone, or most painful for the team. Get it running, measure the results, and use that as the foundation for the next automation. Most clients expand to two or three additional workflows within six months of the first launch.
Do we need to have done an AI Audit first?
No. If you already know which workflow you want to automate and have a clear picture of the pain it's causing, you can start directly with an automation engagement. An AI Audit is helpful if you're not sure where to start or want to prioritize across multiple candidate workflows — it gives you a ranked list of automation opportunities with estimated ROI for each.
—— Field notes
What we’re writing about.
Field notes from the studio — what we’re learning about AI products, agent UX, and the messy reality of shipping software in 2026.
