Most AI tools add a chatbot to something that already doesn't work. We wire AI into your actual operations inside Airtable, with real triggers, real outputs, and a team that actually uses it. Here's exactly how.
See the full process ↓An agentic workflow is an AI that does something on a trigger — not something you have to prompt every time. A lead comes in and it's already researched, scored, and drafted. A report generates itself. A contract gets uploaded and the key terms are already extracted. Your team just sees fewer things to do.
The most common mistake teams make is buying an AI tool and hoping it connects to their work. We start from your work and build the AI into it. The order matters.
The whole engagement, end to end. Every phase has a deliverable, a clear handoff, and a check-in with you. You always know where things stand.
We start by mapping the process, not jumping to the tool. What triggers the work? What decisions happen along the way? Where does data get lost or re-entered? Most teams discover two or three things they weren't planning to automate once we walk through it.
A written trigger map showing the exact inputs, decisions, and outputs for your target workflow. Scope confirmed before anything is built.
We translate the trigger map into an Airtable architecture: which Field Agents handle which steps, where Claude or ChatGPT connects via API, what automations fire and when, and what the output looks like in your base. This is a visual spec, not a vague description. You approve it before we touch your data.
A written architecture document with the model choices, automation triggers, field schema, and fixed price. No surprises during the build.
We build in your existing base, not a sandbox we hand over later. Field Agents get configured, prompts get written and tuned, API connections go live, automations get wired. You have a live link to the base the whole time. We run the workflow against real data and show you actual outputs at the Day 6 check-in.
A working workflow in your live base. Day 6 check-in includes side-by-side before/after comparison of manual vs. AI output so you can see the quality directly.
Edge cases surface at the end, not the beginning. We run the workflow against your actual data variety — unusual records, missing fields, exceptions your process already handles manually. Prompts get tightened, fallbacks get added, and we verify the output quality holds across your real data range, not just the clean examples.
A refined, tested workflow with documented edge case handling. You know exactly what the system does and doesn't do before you depend on it.
We walk your team through the live workflow — how it runs, how to spot a bad output, and what to do if something changes in your process. Every engagement includes a written SOP covering what the workflow does and how each piece is configured.
A live workflow, a written SOP, and a handoff session with the people who will actually use it. Your team is unblocked on day one.
Airtable ships updates constantly. A monthly check-in covers whether new capabilities (like Deep Match or Scheduled Agents) should be retrofitted into your workflow, and whether your process has changed enough to warrant a prompt update. Most clients pick this up after 60 days of running live.
Honest about where Forma is the right call and where it isn't.
We'll walk through your process, show you what Airtable AI can do with it, and tell you whether it's worth building. No pitch, no commitment.
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