Legal work does not happen in legal tools. It happens in Jira, Gmail, a Google Sheet, Notion, a database and one very disciplined bot — all at once. Every sheet below is a real build designed by the lawyer on the matter, drawn the same way: inputs, a control layer, gated outputs. The technology changes; the method does not.
Facts before labels
Start from what actually happens — who signs, who pays, where the data goes — and only then name it in legal terms.
Law that runs through what people already do
Rules go into the tools and steps your team already uses, not into extra signatures and forms.
The smallest change that works
One clause, one rider, one procedure: the narrowest fix that removes the risk.
A human decides, in writing
Every legal call is made by a lawyer and recorded with its reasons. AI drafts and checks; it does not decide.
Evidence boundaries
Each answer says what it rests on and where it stops. Unknowns are named, not guessed.
Independent review
Important documents get a second read against a checklist before they leave.
Real tools, real routes: Jira, Gmail, Sheets, Notion, n8n, Gemini, Drive, a database and a bot. Dashed lines are uncontrolled, manual movement. Solid lines are controlled flow. Every diamond is a gate: nothing passes it unchecked. Each sheet is drawn the same way — map the process, encode the logic, control the output — and Fig. 01 is the master pattern every other sheet wraps around one real build.
The master pattern behind every build: scattered inputs pass one control layer — source of truth, decision rules, validation gates — before anything reaches the outside world.
Workflow schematic: scattered inputs pass through a control layer — source of truth, decision rules, validation gates — and become controlled outputs
Jira, the auditor's mail thread, a Google Sheet and Notion all claim to hold the truth. APIs and n8n pull all four into one database — and the local HTML report becomes the only version everyone trusts.
Data consolidation schematic: Jira and a Google Sheet flow through direct API pulls, auditor mail and Notion flow through n8n, all into one normalized database that renders a local HTML report
Worklogs leave Jira by API, pass hours-and-rate gates, and come back as payout packets in Google Workspace. Anomalies go to a human; approvals and payments get logged.
Payout schematic: Jira worklogs and a rate table enter a payout engine that checks hours against plan and applies rates; anomalies go to a human tray; validated payouts become Google Docs packets, get approved, paid and logged on a monthly cycle
A custom GPT does the first pass on incoming contracts using a versioned knowledge pack — pipeline, risk rubric, anti-overreview rules. Client secrets and personal data stay out; red and amber flags escalate to the lawyer.
Legal bot schematic: contracts from the team enter a custom GPT loaded with a knowledge pack of pipeline, risk rubric, anti-overreview rules and checklist; it maps clauses, scores risk red-amber-yellow-green, outputs a structured review and client-ready draft email; red and amber findings escalate to the lawyer; personal data stays out
One Google Sheet plus approved templates. The merge engine fills, numbers and validates — failures go to a human tray, never to the client.
Document generation schematic: a Google Sheet and template library feed a merge engine; validated output becomes a generated packet with a run log, failures go to an exception tray
The model retrieves from approved sources only, drafts with citations and checks itself — but nothing leaves without a lawyer's sign-off. The model drafts; the lawyer decides.
AI assist schematic: a question and an approved source library feed a model workspace of retrieval, drafting and citation checks; an in-scope gate routes work to a lawyer review gate before an answer with citations is released, out-of-scope questions escalate to counsel
Cron fires at 06:00, webhooks fire whenever. Every n8n flow retries three times, writes a run log and alerts a human only when the duct tape actually tears. The glue is also code — versioned and logged.
Automation glue schematic: cron, webhook and mail triggers enter one n8n flow of fetch, transform and database upsert with an on-error retry lane; outputs are a run log for every execution, alerts on failure only, and data ready for the next step
No envelope goes out before the pre-sign check passes. Signing order is enforced, declines loop back, and executed sets sync and archive themselves.
E-signature schematic: a final draft passes a pre-sign checklist of entity names, exhibits and signature blocks, then moves through an ordered signer chain; declines loop back, the executed set syncs to CRM and archives with an audit certificate
If your contracts, contractors or data also live in four places at once, that is where to start. Sanscript takes your version of it as the lawyer on the matter, writes the rules and hands the system to your team — with a guide to run it on its own.
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