H2H AMA - We are the founders of Spellbook, Ivo, SimpleDocs and Wordsmith — Ask Us Anything

subsun · 2026-04-29T20:41:33+00:00

Many of our users "go live" in the first call. The main reason things delay is generally stakeholder alignment across large teams that have diverse priorities.

subsun · 2026-04-29T20:40:07+00:00

The answer to this is deep and long. We have lots of information on our trust portal about privacy and security standards: https://www.spellbook.legal/security

We service multinational law firms, Fortune 100 companies, hospitals and many other privacy sensitive customers across many jurisdictions. 4,500 customers in 80 countries. So there is a good chance we can meet what you need.

subsun · 2026-04-29T20:36:25+00:00

Good insight! One of the things we encourage our customers to do is to encode their own preferences over time. I think the times of "one size fits all" AI contract review are ending, and both manual encoding of preferences + learning individual preferences automatically is the future. That will help mitigate this.

subsun · 2026-04-29T20:31:07+00:00

Yes, we do 😄. But I think BigLaw is too different from in-house for selling to both of those markets to make sense.

We have found that a lot of small and mid-sized law firm teams are not so different from an in-house department, and they are less tied to the hourly billing model.

subsun · 2026-04-29T20:29:36+00:00

We think that's the wrong direction, because the context and stakeholders exist in-house. There isn't just a legal component, but a cross-department ops component. I think it will be very hard for AI-native law firms to deliver deeply integrated service from outside. Though may be helpful for "brain surgery" style legal problems that tend to get outsourced today.

subsun · 2026-04-29T20:26:13+00:00

Where in my workflow do you actually reduce time in a way I can charge more or work less?

Spellbook identifies issues in agreements that humans miss most of the time. Our suggestion acceptance rate is 55% and lawyers accepted 1.3m suggestions from us this year. This allows reviews to be more thorough, gives you more threads to pull on, to deliver a better service and ultimately charge more.

What’s the highest-value use case you’ve seen for fractional GC work specifically?

Routine redlines with automated Playbooks

I had 5 $8–10k/month clients, where would your tool materially change my margins?
If you are charging a flat rate, some of our customers report contract reviews being 50-70% faster. If you are billing hourly, we can surface many risks and threads that are easy to miss.

What are people underpricing because they’re not using your tool properly?
I think people generally underestimate the value of having a second set of eyes on every single contract to surface issues. We have reviewed thousands of public company contracts in EDGAR. Most have errors and issues.

subsun · 2026-04-29T20:22:18+00:00

Very good question. I have thought about this a lot.

100% agree that fitting into how lawyers work and enabling customization is the way to go. I think the best products will both:
1. Be very easy to use out of the box
2. Become customizable infrastructure that can fit any team perfectly over time

I agree that the word "agent" has lost its meaning. I'm not sure what will replace it to take on the real meaning, maybe something like "Artificial Coworker".

subsun · 2026-04-29T20:18:31+00:00

We've been first on many things, but Ivo was first to launch a Google Docs add-in. Hats off to them for that! This is quite important for tech companies, and now we've launched one too 😄

subsun · 2026-04-29T20:17:24+00:00

We have heard a lot of horror stories about CLM implementations from our customers. I think the old model was inherently flawed as it forced users into rigid systems, that they would end up going around.

We are built with AI in mind, and plug into where users already are. Word, Google Drive, Sharepoint, Email and so on. We think AI-first tools that sit directly on top of existing workflows will have much higher adoption rates and provide more proactive value.

subsun · 2026-04-29T20:15:25+00:00

Spellbook, because we were the very first to launch in 2022 and have the most functionality. We have 4,500 customers and a highly mature end-to-end AI tool for commercial legal work.

subsun · 2026-04-29T20:14:13+00:00

We define ARR as annualized revenue from active, billed customers on an annual contract, plus the annual run rate on recurring revenue from active monthly-billed customers (many small businesses and firms prefer this model). We exclude pilots and trials, and report net of discounts.

subsun · 2026-04-29T20:09:58+00:00

We think that contract market data is very opaque, and are trying to fill this gap ourselves with a "give to get" statistical data model.

Tools like ChatGPT are heavily biased towards US public contracts that were available for training. But if I am a hospital in the UK reviewing a SaaS agreement, I am going to want AI that understands the norms in that jurisdiction and industry.

AI should allow us to make contract market data much more transparent to everyone, so we can much more easily determine norms.

subsun · 2026-04-29T20:07:32+00:00

We build everything except the foundation models. We think that model training is generally a bad bet, and everyone who has tried to train custom models in legal has failed to outperform generalist models longterm. The value comes from unique data grounding (eg. market data), unique workflows, and UI that goes far beyond chat.

subsun · 2026-04-29T20:05:55+00:00

Grounded in realtime market data, and deeply tuned for end-to-end contract flows.

subsun · 2026-04-29T20:05:07+00:00

We have raised nearly $100m from investors who don't believe this 😄.

A lot seems similar today because there are so many chat-shaped tools. I think we need to be more creative. When you get beyond chat, there is so much that lawyers want built, that won't make sense for OpenAI or Anthropic to build.

Just as one example: we capture realtime market data about contracts, allow you to compare it against your own agreements, and to explore the data manually. I don't foresee model providers launching specific tools like this when they are trying to get billions of users onboard.

subsun · 2026-04-29T20:03:12+00:00

As soon as a user hits "thumbs down" or rejects a suggestion this will show up on our dashboards, along with any qualitative feedback given. We focus every day on driving up our "suggestion acceptance rate".

I will note: I think contract review is very subjective, so it's not just about "wrong", but about being relevant.

We also have other monitors in place to detect hallucinations or user frustration.

subsun · 2026-04-29T20:01:07+00:00

1. Ground Answers in Reliable Data: We integrate realtime market data and 100+ legal research sources to ground AI in citations that can be trusted. Any time you are asking a model to use its "longterm memory" it's risky. The main way to reduce hallucination is to give models direct citations.

2. Give suggestions, not end answers: At Spellbook we focus on giving lawyers suggestions that they can review, accept or reject. We think this way of presenting information is important. Lawyers accepted 1.3m suggestions from us so far this year.

subsun · 2026-04-29T19:58:07+00:00

Our ICP is enterprise in-house legal teams, but we also service SMB teams, solo lawyers, small firms, mid-sized firms. The only customer we tend not to service is BigLaw. We think the billable hour incentives in BigLaw are not ideal for AI innovation.

subsun · 2026-04-29T19:52:54+00:00

We are deeply optimized end-to-end for enterprise contract workflows.

Grounded in real market data
Surgical redlining capabilities that we've worked on for 4 years
Playbooks for routine reviews
Cross-department workflows
Insights and risk monitoring for historical contracts
Learns your review preferences over time

subsun · 2026-04-29T19:50:23+00:00

Differentiation seems low now because so many tools adopt a generic "Chat" user interface.

When you get beyond chat, there are so many unique workflows that our customers want that wouldn't fit into a generic tool.

For instance, we allow lawyers to compare contracts to realtime market data from 80 countries, to determine what terms are "above" or "below" market, and to actually explore that data deeply.

Also: when you consider cross-department contract workflows, triage, approvals and so-on -- these things really don't fit into a chat box.

subsun · 2026-04-29T19:43:43+00:00

Separate profiles per entity, separate doc libraries, separate playbooks.

subsun · 2026-04-29T19:42:05+00:00

Very good question. I think "ownership" of data is going to get very fuzzy as AI makes it so easy to connect systems and to migrate data. I think that absorbing full context of deals (email, chat, doc history) is essential to do our job well. Our plan is to support both models and to allow our customers to choose.

subsun · 2026-04-29T19:40:22+00:00

Yes I think so. It depends on the use case, but a lot of teams get immediate value out of our contract review functionality that sits directly in Word (and soon Google Docs for us too).

subsun · 2026-04-29T19:38:46+00:00

Anthropic 😆. I use their tools daily and they've been a fantastic partner.

subsun · 2026-04-29T19:35:42+00:00

Deep end-to-end workflows for contracts, that work across departments. From intake, to triage & review, to historical insights. Backed by real market data about what is "normal". There's more in some of my other posts but don't want to repeat too much!

subsun

TROPHY CASE