For legal operations teams

Your playbook lives in a wiki.Your reviews don't follow it.

Taiso checks every clause in every agreement against the playbook position it should match — escalates only the deviations your counsel needs to see, and records why each one was accepted. Same lawyers. Every contract covered.

Encode one playbook as an SOP →See it run on an agreement
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Start with Taiso Verify on a single workflow — no migration, and nothing new for your team to learn. Scale to the Taiso Agent Control Platform — your whole contracting operation, verified.

The gap between the playbook and the review

You wrote the positions down.
Nothing checks that they were applied.

Two to five lawyers are the bottleneck for every NDA, DPA and MSA the business signs. The queue is the roadmap.
Your playbook says what to accept. Whether a given redline followed it depends on who reviewed it and how late it was.
Legal used AI on a first pass and quietly stopped, because nobody could show which clauses it actually read.
When a term surfaces in a dispute, there is no record of who accepted it or what position it deviated from.

A playbook nobody enforces is a document, not a control. The difference is whether something checks every agreement against it.

See it run — one hundred agreements

Watch every clause get checked.
Not a sample.

A two-and-a-half-minute walkthrough of one hundred inbound agreements — narrated by the legal-ops lead who owns the queue.

STEP 1 OF 6Your contract queue today
NarratorOne hundred agreements land in the legal queue today.
Inbound · 100 agreements10 fully reviewed · 90 skimmed
Taiso verification gate — every clause checked against your playbook position, before the agreement is signed
read by a lawyersigned after a skimchecked against sourcethe unconfirmed few
90agreements signed after a skim, not a review
10agreements a lawyer actually read end to end

The ninety nobody read closely are the ninety you're bound by.

0of 100 checked against your playbook
confirmed0
the machine couldn't confirm0

No lawyer re-reads a standard clause.

Agreement 84 of 100Master services agreement — liability cap
The counterparty's draft says$250,000
Your playbook position is“Liability capped at fees paid, with a floor of $1,000,000; anything lower requires counsel sign-off.”
VerdictDISPUTED · held for a human
A deviation from your own position, signed on a busy Friday. This is the clause that gets read for the first time during a dispute.
Counsel queue0
Your lawyers see these ten deviations — not all one hundred agreements. The same hours you spend skimming today, spent on the terms that actually deviate.
Playbook trail0 / 100
confirmed0
accepted by counsel0
signed after a skim0

The record that shows which position applied, and who departed from it.

Playbook in a wiki10 deviations signed — read again during a dispute, if ever. Your lawyers skimmed the rest.
Playbook as a control0 agreements signed unchecked · 10 deviations accepted by counsel · 100 on the trail. Same legal hours.
Encode one playbook as an SOP →
←/→ step through · space plays · V mutes

Illustration of the mechanism on a hundred inbound agreements. Volumes and counts are illustrative, not measured results — the exception rate most of all. How many items actually need a person is the number the parallel run measures on your own work, and it is the number that decides whether the hours hold.

How the playbook runs

Five checks
on every clause.

01
Intent
Does the clause do what its heading says it does?
an indemnity hidden inside a support-terms exhibit → mismatch
02
Evidence
Is the position in your playbook, or did the model infer it?
liability floor located in playbook section 4 → supported
03
Policy
Does the deviation follow your approval matrix?
uncapped indemnity accepted without counsel sign-off → blocked
04
Risk
What does this term cost you if it's wrong?
liability cap below the playbook floor → counsel decides, not the model
05
Audit
Is the acceptance recorded, sourced and replayable?
clause, playbook position, verdict, approver, timestamp → playbook trail

Five checks, one verdict — ALLOW — before the agreement is signed.

Sound like your week?

Why the playbook
keeps getting ignored.

THE QUEUE IS THE ROADMAP
Legal is the bottleneck on revenue
Deals wait on contract review, and the only lever you have is asking two lawyers to read faster.
AI STOPPED AT THE PILOT
Fast, cheap, unverifiable
It read the contracts. Nobody could show which clauses it actually checked, so it never touched a signed agreement.
A TERM SURFACED LATE
And nobody knew who accepted it
The clause deviated from your own playbook. Finding out why took longer than the negotiation did.

If two of these are true, the pilot below was built for you: agreements you have already signed, and nothing in the live queue changes.

What your playbook actually reaches

You wrote the positions.
Nothing was checking them.

10%
of agreements that get a real read
100%
checked against your playbook
0
agreements signed on a skim

The playbook does not change. Whether it is applied stops depending on who was free on a Friday.

Before you roll it out

What legal asks
before this goes live.

YOUR CONTRACT DATA
Agreements stay inside your boundary
Deploy in your own environment, or hosted under a DPA with a no-training clause and retention you set.
YOUR CLM STAYS
It reads the repository you already run
Your contract system keeps the workflow, the storage and the signature. The gate checks clauses against your playbook and routes deviations to counsel.
YOUR LAWYERS
Two to five people, aimed at what moved
Standard terms stop consuming legal hours. Counsel sees the deviations, with the position they departed from already attached.

On certification: SOC 2 Type I is on the clock, and Type II is what most financial buyers gate on — we are not going to pretend otherwise. Closed work is still confidential data, so the pilot runs under NDA and a DPA, in your environment or ours, and goes through the same security review your clients require of any new processor. We will fill in the questionnaire.

What the team keeps

The playbook compounds.
The next negotiation starts ahead.

PLAYBOOK TRAIL
Who departed from which position
Every accepted deviation with the playbook position it departed from, the verdict, and the approver — attached to the agreement, not reconstructed in discovery.
YOUR PLAYBOOK, EXECUTABLE
The wiki becomes the control
Your positions stop living in a document people consult when they have time and start running as the thing that checks every clause.
DEVIATION PATTERNS
What you keep conceding
The trail shows which positions get negotiated away most often — which is the input your next playbook revision has never had.

By day 3 you see what it would have flagged in agreements you have already signed. By day 14 you have the trail and the deviation list — yours to keep either way.

The offer

One playbook.
One hundred signed agreements.

Give us your playbook and a set of agreements you have already signed, under NDA. We encode the positions and run them in parallel — nothing in your live queue changes — and we hand back every deviation we found, what a skim missed, and what we got wrong. Bounded defect rates with the sample size beside them, never a zero-miss promise.

Encode one playbook as an SOP →Read the docs