01
Client context
Summarize preferences, constraints, inspiration, budget posture, and decision history before meetings.
Interior design studios
Use AI to organize decisions without flattening your taste — with control.
Datum helps design teams apply AI to the coordination work around client context, selections, presentation prep, procurement notes, and follow-up.
Measured at KBF Design Gallery — the firm Datum is built inside
7 hrs → 30 minper scope of work after one week of build
490 hrsreclaimed per year from a single task
$5.2M → $13.8Mdesign-build revenue, 2021 to 2025
+20%revenue capacity with no new hires
Free resource / start here
Watch it work
Watch the scope write itself.
Sample output from the scope workflow Datum built inside KBF — a 7-hour task drafted in seconds, ending where it should: a draft with flags for human review. Taught on the real tools: Claude and Claude Code by Anthropic, ChatGPT and Codex by OpenAI.
Pick a project type above — a reviewable draft assembles in seconds.
Illustrative sample, streamed in your browser — not a real client file. Every real run ends the same way: a draft with flags, reviewed by a human before it touches a customer.
Build this for your business →
01 / First workflows
Start where AI creates leverage first.
These are not finished automations handed away for free. They are the safest first categories to map, test, and operationalize inside the Foundations of AI cohort or a Discovery Call.
02
Selection tracking
Track open decisions, vendor questions, lead-time risk, and client-ready summaries.
03
Presentation prep
Draft product notes, comparison language, and meeting storylines for designer refinement.
04
Follow-up
Turn meeting notes into next actions, reminders, and recap drafts.
02 / Guardrails
Grounded, reviewable, and useful.
Datum teaches AI as controlled workflow design, not an open-ended assistant wandering through the business.
Ground the AI in sources.
Client notes, selection schedules, vendor PDFs, presentation decks, inspiration images, and approved brand voice examples.
Keep the risk boundary clear.
Do not ask AI to replace taste, approve specifications, or invent product facts not grounded in vendor sources.
03 / Related verticals