AI & Agentic Workflows
Practical AI that does real work. We build AI-powered tools and agentic workflows that automate multi-step processes, connect to the systems you already run, and keep people in control.
What are agentic workflows?
Most AI tools answer questions. Agentic workflows take action. An AI agent can read an incoming document, look up the right records, make a routine decision, update your systems and hand anything unusual to a person, all as one automated process. Paired with well-built custom software, agents can take on the repetitive, multi-step work that used to mean someone copying data between screens.
Where AI fits in your business
The best opportunities are high-volume, rules-heavy tasks that still eat up staff hours: reading and entering data from invoices, purchase orders and emails; drafting quotes, reports and customer replies for review; answering questions from your own documents and data; routing and triaging requests; and reconciling records across systems like QuickBooks, your ERP or a legacy database.
Why build custom instead of buying an AI tool?
Off-the-shelf AI tools are generic, and they rarely connect to the systems your business actually runs on. A custom solution is built around your workflows and your data, works with your existing software, and keeps sensitive information under your control. You decide what the AI handles on its own and where a person signs off, and you own what we build.
Where should we start with AI?
Start small and measurable. We help you pick one workflow with a clear cost today, such as hours spent on manual data entry, build an agent to handle it, and prove the return before expanding. Most businesses get more value from one well-integrated agent than from a dozen disconnected AI subscriptions.
What AI and agentic workflows get you
How we build AI and agentic workflows
We use the same proven process as every Steelhead project:
1. Discovery: Identify the workflows where AI will deliver a measurable return, and the data and systems involved.
2. Design: Map how the work happens today and design where the agent acts and where people review.
3. Build: Build the agent and connect it to your systems, starting with the highest-value task.
4. User Acceptance Testing: Your team tests the agent against real cases before it handles live work.
5. Launch: Roll out gradually, with monitoring so you can see exactly what the agent is doing.
6. Continuous Improvement: Measure results, refine rules, and expand to new workflows as the return proves out.
Sally Clipfell, Controller - Cascade Meats
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