The stack for the two-to-six-lawyer in-house department that already has a CLM and is now deciding what AI to put on top of it. The CLM solved routing and storage. It did not solve the two things that still consume the team: reading counterparty paper, and answering the business’s questions fast enough that the business stops routing around legal. This stack assigns those two jobs to separate tools, keeps the CLM as the system of record, and names the loop that stops the AI layer from drifting away from the department’s actual positions.
How the pieces fit
Ironclad is the spine: intake, routing, approvals, repository. Every request enters through a structured intake form rather than an email to the legal alias — counterparty, agreement type, dollar value, requested terms, target date. Routing rules tier the request: standard-form NDAs and low-value vendor agreements go to a self-service track that never reaches a lawyer; anything on counterparty paper, above a value threshold, or touching data processing routes to the attorney queue pre-tagged. Post-signature, the executed agreement lands in the repository with renewal and termination dates indexed. Ironclad is quote-based and its 2026 release added Ironclad Assistant, an agentic layer that handles lifecycle tasks inside the platform. Treat that layer as workflow automation, not as your review engine — it operates on contracts already inside Ironclad, which is the smaller half of the problem.
Ivo is the third-party paper review engine. The handoff from Ironclad is the attorney-queue trigger: a request tiered as counterparty paper routes to Ivo, which reads the document against the department’s playbook and returns an issues list — which clauses depart from your positions, how far, and what redline to propose. The lawyer accepts, edits, or overrides. Ivo’s value is concentrated in volume: a department seeing 40 or more third-party agreements a month recovers enough attorney hours to pay for it, and below roughly 15 a month it does not. Ivo raised a $55M Series B in January 2026 and does not publish pricing — its pricing page returns a 404, and every deal is quoted. Budget for a per-seat annual contract and ask for the volume tier in writing.
GC AI is the counsel-facing copilot for everything that is not a contract review. The handoff is the question, not the document: when the business asks whether a marketing claim needs substantiation, whether a termination-for-convenience notice period runs from receipt or from sending, or what the department’s position on uncapped data-breach liability actually is, GC AI answers with citations and drafts the memo. It also handles first drafts of policy, board summaries, and diligence questionnaire responses. GC AI publishes its entry price — $500 per seat per month on the Individual plan with a 14-day trial and no seat minimum, with Team and Enterprise quoted annually. That published number is the reason it is the easier first AI purchase: a two-lawyer department can run a real pilot for a month at $1,000 with no procurement cycle.
DocuSign IAM is execution and the agreement record for everything outside legal’s queue. The handoff from Ironclad is the approval-complete trigger: final terms leave the CLM, execute in DocuSign, and the executed artifact plus its metadata writes back to the Ironclad repository. The second job matters more than the first — HR offer letters, procurement POs, and sales order forms are agreements that never enter the legal queue and never should. DocuSign IAM is where those live, which means the department can answer “what did we sign” for the whole company rather than for its own queue. DocuSign’s published web plans price per user with volume breaks: about $50 per user per month at five users, falling to about $30 per user per month at fifty, billed annually, across IAM Starter, Standard, and Professional tiers, with IAM Core quoted for larger deployments.
Notion is the playbook that the AI layer reads from. This is the component teams skip, and skipping it is what makes the AI layer decay. The department’s fallback positions, approved clause language, escalation thresholds, and the record of which deviations were approved and why all live in one Notion database. It serves three consumers: the business, self-serve, so routine questions never become tickets; Ivo, as the source the playbook configuration is derived from; and GC AI, as the context that makes its answers reflect your positions rather than generic market practice.
The loop that keeps this from decaying
The handoff chain runs request → Ironclad tiering → Ivo review or GC AI answer → negotiation → Ironclad approval → DocuSign execution → repository. That chain is the easy part; most vendors will draw it for you in a diagram.
The chain that actually determines whether the stack is worth its cost runs backwards: a lawyer overrides an Ivo suggestion or rejects a GC AI answer → the correct position is written to the Notion playbook that week → the Ivo playbook configuration and the GC AI context are updated from it → the next review applies it. Without that write-back, both AI tools keep proposing the position the department abandoned six months ago, lawyers learn to ignore their output, and within two quarters you are paying for two AI licenses that produce suggestions nobody reads. Assign the write-back to a named person with a weekly slot. It is 60 to 90 minutes a week and it is the difference between this stack working and this stack being shelfware.
Cost reality
For a four-lawyer department with roughly 600 agreements a year:
- Ironclad: quote-based, commonly $50,000–$120,000/year at this scale, plus $10,000–$25,000 first-year implementation.
- Ivo: quote-based, no published price. Expect a per-seat annual contract in the same order as other AI review tools at four seats.
- GC AI: $500/seat/month published on the Individual plan; four seats at list is $24,000/year, less on an annual Team contract.
- DocuSign IAM: roughly $30–$50 per user per month on published plans depending on seat count, billed annually. Ten users lands near $5,400/year.
- Notion: Business at about $20/seat/month annually. Eight seats including business stakeholders is roughly $1,900/year.
Total: roughly $110,000–$220,000/year, with Ironclad the dominant line and the AI layer adding $30,000–$60,000 on top of it. Two cost notes the vendors will not volunteer. First, buy one AI tool, not two — a department under 40 third-party agreements a month should run GC AI alone for two quarters and add Ivo only when the review backlog, not the question backlog, is what the lawyers complain about. Second, the Notion playbook maintenance is real labor at 60–90 minutes a week; if nobody owns it, cut the AI layer rather than paying for it unmaintained.
Match rules
This stack is the right pick when:
- The department is 2–6 lawyers with a CLM already deployed and paid for
- Annual agreement volume is 300–1,500, with a meaningful share on counterparty paper
- The business complains about legal turnaround time more than about legal’s judgment
- There is one person willing to own the playbook write-back
This stack is wrong when:
- There is no CLM yet — buy the CLM first and run it for two quarters before adding an AI layer, or you will automate a routing process you have not defined
- The department is one lawyer — the legal ops team-of-one stack is the right size, and this one over-buys the review layer
- Volume is under 200 agreements a year — the AI layer will not clear its own cost, and a well-maintained template set does more
- The department’s problem is outside-counsel spend rather than in-house throughput — that is a matter-management and billing problem, not an AI-review problem
Common variations
Run DocuSign IAM as the spine and drop Ironclad. If the company already standardized on DocuSign across HR and procurement and legal’s workflow needs are modest — under five agreement types, approvals that are one or two steps — IAM’s workflow layer covers enough that a second CLM is redundant spend. Rule for the swap: choose this when the count of distinct approval paths is under five and no one needs obligation tracking after signature. Choose Ironclad when post-signature obligations, renewals, and reporting are the reason you are buying at all. The head-to-head is in Ironclad vs DocuSign IAM.
Swap Ivo for Spellbook when drafting outweighs reviewing. Ivo is built around reviewing paper you did not write; Spellbook sits in Word and is stronger when the department is generating first drafts from its own templates. Rule for the swap: if more than half the department’s contract hours go to drafting your paper rather than marking up theirs, Spellbook fits the workflow better. See Ivo vs Spellbook.
Drop GC AI and use Claude directly. For departments that will not maintain a legal-specific context layer, a general assistant at $20–$100/month covers memo drafting, summarization, and policy work at a fraction of $500/seat. Rule for the drop: take this path when the department’s questions are mostly drafting and summarization rather than substantive legal guidance where citations matter. The tradeoff is real — you give up the citation and legal-source grounding that is the reason for GC AI’s price.
What this stack does NOT replace
- Outside counsel for litigation, securities, employment disputes, and specialist regulatory work
- Matter management and outside-counsel billing review — Brightflag or an equivalent is a separate purchase, and this stack does nothing about legal spend
- Legal research on novel questions — GC AI answers within its sources; Westlaw, LexisNexis, or Thomson Reuters CoCounsel remain the research layer
- eDiscovery — active litigation with document volume needs Relativity or Everlaw, not a CLM repository
- The lawyer’s judgment on the deviations that matter. Both AI tools are calibrated to the playbook, which means they are silent on the risk nobody wrote down yet. Every issues list is a starting point for a lawyer, not an output to forward to the business
- Compliance program tooling for SOC 2, ISO 27001, or GDPR programs — those integrate with this stack but are not covered by it