Software projects are notorious for blowing past their projected timelines. Despite numerous techniques to try to mitigate this, delays and cost overruns are the norm, and have been forever. This is illustrated by such phenomena as the Ninety-Ninety Rule:
The first 90 percent of the code accounts for the first 90 percent of the development time. The remaining 10 percent of the code accounts for the other 90 percent of the development time.
Most software projects follow a long-tailed lifecycle. In the beginning, progress is fast as the basic functionality is built out. Whether you're building a peer-to-peer networking library, an AI contract review product or a self-driving car, you can probably quickly knock out something demo-ready. You might even convince people to buy it! But there will be bugs - holes in your logic, or edge cases you haven't considered. Your demo software will be filled with bugs, and your typical user will complain that your software is "crap."
The process of going from demo software to mature software is the process of hammering down the long tail of bugs. How long will you have to hammer for? It depends on the domain.
A wise man once said:
grug understand all programmer platonists at some level wish music of spheres perfection in code. but danger is here, world is ugly and gronky many times and so also must code be
The insight we can draw from Grug's words is that, the closer your problem is to the "ugly and gronky" real world, the longer and fatter the tail will be.
Self-driving cars are very close to the real world, so their tail is long. The DARPA Grand Challenge was in 2004, and after twenty years of hammering down the tail, Waymo still only operates in five cities. Peer-to-peer networking libraries only have to deal with other computers, so their tail is relatively minuscule - Bitcoin is still running on the same chain debuted by Satoshi Nakamoto in 2009.
Ivo's domain sits in the middle. We’re not driving cars, but after decades of evolution, Microsoft Word barely qualifies as "software" anymore - rather it's some semi-organic digital lifeform that no human fully understands. Contracts, while they bear deceptive resemblance to trees and other familiar datastructures, are unapologetically and often deliberately flawed human constructions. And LLMs...don't get me started on LLMs.
The result of this is it's easy to build demo-ready contracting software, but the road to non-crap contracting software involves hammering down a very long tail.
In 2014, I interned on a self-driving car team. The engineers had a team-wide mandate to increase our "Miles-Per-Intervention" (MPI) to 1 million. My memory is fuzzy, but when I joined, I think our MPI was around 0.7. Every week, we would have an org-wide meeting where we went through every single incident where a human driver had had to intervene.
All sorts of stuff came up in the meeting. There was one t-junction in Mountain View where the double-yellow lines extended out pretty far, and rather than risk clipping the painted lines as it cut the corner, the car would just stall forever. There was another intersection where the setting sun would reflect off the red traffic light, making it look active even when the light was green. Also, one time, they took the car to Arizona and it thought all the cactuses were people.
All the interventions were filed as bugs and assigned to the appropriate teams, who would diligently fix them. Fixing some of these bugs was hard. Entire modules had to be written, others thrown away, others endlessly tweaked. By the time my internship ended, the combined efforts of all these dozens of brilliant hard-working people had pushed our MPI to slightly above 1.
The main reason why there aren't that many self-driving car companies is because most software teams don't have the patience or diligence to take on a multi-decade bugfixing marathon. It's much more satisfying to work far away from the real world and chase music of spheres perfection. At Ivo, we're grateful that our domain isn't as long-tail as a self-driving car. Still, in a domain where it's easy to build a demo-ready solution, our willingness to spend months and years hammering down the tail is our biggest competitive advantage.
Our threshold for what qualifies as a "bug" is very low. Basically, any time our software does something worse than a human, it's a bug - even if it hasn't done anything technically "incorrect".
After the redlines have been applied and the changes have been accepted, all of these diffs result in the exact same text in the document. They all do the same thing, so in a sense, they're all "correct." But the leftmost diff is unnatural. It's noisy and hard to understand. Moving from the leftmost screenshot to the middle screenshot took us around a year and a half of iteration on a "diff coalescing algorithm," which we hammered down bug report after bug report. Our diff.js file is now over a thousand lines, and diff.test.js is even longer.
The middle screenshot still has a problem though - the words "if Metadata becomes aware of a" are redundantly removed and reinserted. This is a particularly tricky case because the string "if Metadata becomes aware of a" constitutes the suffix of the deletion and the prefix of the insertion, so even though the redundancy is obvious to a human, it's hard for a computer to efficiently detect. This bug was assigned to our newest full-time engineer, and he was able to figure out a clever way to modify the KMP algorithm to detect the redundancy in linear time and coalesce it into the final result on the right.
The reason that Ivo has the best redlining on the market has nothing to do with AI, and everything to do with an extraordinarily talented engineering team who is willing to spend years diligently hammering down the long tail.
Do you want to build something great too? Join us!
The Ivo team joined thousands of legal professionals in Philadelphia recently for the Association of Corporate Counsel Annual Meeting. The team met dozens of lawyers and legal ops professionals in every industry and working for companies of every size, and a prominent theme that emerged is that small, lean legal teams are overwhelmed with high volumes of work and are hoping that AI can help.
In numerous conversations that the team had with legal professionals, we heard the same stories over and over again:
For us, there were three key takeaways:
We hear the message loud and clear: The market for legal tech has matured at an incredible rate in the last few months. Teams want to use AI to clear out their workloads, and want to understand what technology is available and guidance on how to select tools.
Take a look at this webinar to get more advice on how in-house counsel should use AI tools.
F5, a technology leader specializing in app delivery and cybersecurity, has partnered with Ivo to streamline and simplify its contract review workflows. Ivo’s ease of use, integration into the team’s existing workflows, and the breadth of features were cited as reasons why F5 chose to partner with Ivo.
Many technology companies struggle with managing complex contract review workflows while ensuring consistency and accuracy. In addition, legal teams must work with complex contract amendments which often include large volumes of new terms.
Ivo’s ability to analyze and ensure consistency across multiple documents as well as the ease of use and integration into existing workflows leads to greater efficiency and ease in managing contracts. Plus, Ivo’s approach of training its AI models with custom-built playbooks, created by lawyers, leads to not only standardizing processes across companies, but allows for a personalized approach to contract review.
“We’re thrilled that a company like F5 has chosen to partner with Ivo to streamline and standardize their contract review workflows,” said Min-Kyu Jung, the CEO and co-founder of Ivo. “For technology leaders, speed is a competitive edge. The efficiency gains that F5 will experience as a result of re-imagining their contract workflows will help their legal team spend their time on more strategic outcomes for the business.”
F5’s partnership with Ivo highlights that there’s no need to make a choice between efficiency and accuracy. Rethinking the tedium of manual contract review means that legal teams can spend their time on strategic work that will contribute to the business’ bottom line.
See a demo to find out how Ivo could be part of your workflow.
Ivo Assistant is an exciting and powerful feature in our product because it allows you to ask plain-language questions about your contracts just like you would ask a colleague. Assistant is an agentic legal partner that allows you to review, redline, and get instant answers from your contracts and trusted sources using ordinary language prompts. When combined with Repository, you can get immediate insights, discover risks, and track patterns across all of your agreements.
Our customers love Assistant because it’s such a powerful tool that’s also easy to use. But, like any AI tool, if you prompt it well, it will give you better answers than if you prompt it poorly.
Here are the top 10 secrets to great prompts for Ivo Assistant:
1. Define your goal. Before typing your prompt, ask: What am I trying to achieve?
- Good: Summarize this 10-page contract into five key takeaways for executives.
- Not-as-good: Summarize this.
2. Provide context and constraints. AI works best with background, audience, and boundaries.
- Good: Draft an email memo for my sales team. Be sure to include details about the deal size, contract term, and any other context that would be relevant to a sales organization.
- Not-as-good: Draft an email for my sales team.
3. Specify tone, style, or role. Assign a persona to shape the response:
- Good: Act as a product trainer. Explain how the new repository feature works in simple steps.
4. Break down complex requests into simple ones. Split complex requests into steps for clarity.
- Good: 1) Generate subject lines → 2) Draft email → 3) Refine.
5. Iterate and refine. First drafts are rarely final. Don’t be afraid to follow up.
- Examples: “Make it concise.” “Add 3 data points.”
6. Use examples and templates. Show what good looks like. Examples act as guardrails and improve accuracy.
7. Experiment with prompt styles. Try direct instructions, open-ended questions, or comparative framing.
8. Watch out for pitfalls. You want to make sure that your prompts aren’t too vague, because you’ll get generic answers. Avoid prompts that are too long, because the tool may miss details. And if your prompts are unclear, the answers may be off-target.
9. Consider some helpful prompt frameworks:
- Role + Task + Context + Format + Tone
- C.R.I.S.P.: Context, Role, Instructions, Specifications, Purpose
10. Remember the Golden Rule. Treat AI like a smart junior lawyer, not a mind reader. Give it clear instructions, check its work, and refine.
As a cheat sheet, here are the top five things to think about when creating great prompts:
Take a look to see more of what Assistant can do for you.
The Aldo Group, a leading multinational retailer specializing in shoes and accessories, has chosen Ivo to accelerate and streamline its review contract. The in-house legal team was excited to select Ivo to ensure consistency and speed across all of its contract review workflows.
Retailers deal with dozens of contracts, if not more, on a daily basis. And for a retailer that operates across multiple countries like the Aldo Group, a universal approach to documents is very important. Ivo’s implementation of custom playbooks with our customers’ own standard terms means that customers can ensure consistent application of their own positions every time. And of course, having the standard positions already implemented in Ivo means the tool can detect and flag deviations from those positions for a lawyer to review quickly and easily.
We are proud to work with The Aldo Group as they re-imagine their contract workflow for speed and consistency across their global team, said Min-Kyu Jung, the co-founder and CEO of Ivo.
Ivo’s contract review platform allows legal teams to review contracts up to 75% faster while maintaining their unique standards and positions. Ivo reads and interprets complex contracts exactly as a lawyer would, providing surgical redlines directly in legal teams’ existing workflows.
A growing number of retailers are implementing Ivo to make their contract workflows simpler and more consistent. Ivo delivers accurate, precise redlines in a fraction of the time it takes to manually review contracts, helping legal teams work smarter, not harder.
Learn more about how Ivo could help your company transform contract review here.
Backblaze, the leading open cloud storage platform, has selected Ivo to streamline its contract review workflows. The company’s in-house legal team will use Ivo to end time-consuming manual reviews and create efficiency and scale as the company continues to grow.
The legal team at Backblaze wanted to solve the often laborious contract review process. In-house legal teams are interested in simplifying repetitive processes like reviewing counterparty redlines or third-party paper. Ivo can also generate issue lists and executive memos for large deals.
Min-Kyu Jung, CEO & Co-Founder of Ivo, noted:
“We are proud to partner with Backblaze as they embrace AI to transform legal workflows. By choosing Ivo, their team is investing in efficiency, effectiveness, and the ability to focus on the highest-value outcomes.”
Ivo’s platform enables legal teams to review contracts 75% faster while maintaining their unique standards and achieving time-to-value through rapid implementation. In-house legal teams appreciate Ivo’s purpose-built AI that understands complex legal documents with lawyer-like precision. In other words, Ivo’s AI understands your contracts as a lawyer does, dramatically speeding up contract review without compromising accuracy or context.
The efficiency benefits that come from implementing a modern contract review process include building a strong foundation to scale and increase strategic impact. In addition, Ivo’s custom playbooks offer surgical redlines and rapid, consistent insights that accurately reflect your legal standards.
Learn more about how Ivo is partnering with legal teams across industries.
After an extensive evaluation process, Reddit selected Ivo for its contract review and repository capabilities. With Ivo, Reddit’s legal team will streamline its review processes, improve contract insights, and drive business impact.
Traditional contract management systems are difficult to maintain and often rely on manual tagging, which is expensive, time-consuming, and prone to error. Attempts to automate this with CLMs have largely failed, as traditional CLMs lack robust search and data retrieval capabilities.
Contract management should be efficient, insight-driven, and effortless to manage. Ivo’s purpose-built AI engine, AiRE, powers its Repository: automatically extracting, linking, and clustering contract data without the need for manual tagging, setup, or maintenance. Legal teams can instantly query their contracts for insights that inform strategy and strengthen operations.
In addition, Ivo’s native integration with Microsoft Word and other tools legal teams already use minimizes workflow disruption and delivers rapid time to value. The ability to work within familiar systems makes adopting Ivo effortless.
“Technology leaders like Reddit recognize that legal teams have a strategic impact on their business,” said Min-Kyu Jung, CEO & Co-Founder of Ivo. “Reddit’s investment in Ivo is an investment not only in speed and efficiency, but also in insights that drive powerful business outcomes.”
Companies that use Ivo see up to a 75% efficiency gain in contract review—an advantage that’s critical in industries where speed defines success.
Ivo is transforming contract review and management for companies across tech and beyond. Learn more about Ivo’s impact.
Lemonade, America’s top-rated insurance company, has joined the rapidly expanding list of companies using Ivo. Ivo’s AI-powered contract review tool will allow Lemonade to generate precise, accurate redlines while reducing the time spent manually reviewing contracts.
Like many in-house legal teams, Lemonade needed a solution to speed up its laborious, manual contract review processes. Lemonade’s in-house legal team evaluated many AI-powered solutions before choosing Ivo. Ivo’s platform received top marks for accelerating their contract review processes by 75%, while achieving fast time-to-value with implementation that takes just one to two weeks. In addition, Ivo’s custom-built playbooks offer rapid, surgical redlines and consistent insights that accurately reflect each company’s unique legal standards. Lemonade will use Ivo to, among other things, review vendor agreements, including redlines of their form agreements.
Min-Kyu Jung, CEO & Co-Founder of Ivo, noted:
“We are proud to partner with Lemonade as they embrace AI to transform their legal workflows. By choosing Ivo, their team is investing in the ability to focus on the highest-value outcomes and to achieve strategic impact.”
In-house legal teams appreciate Ivo’s purpose-built AI, which understands complex legal documents with institutional knowledge and surgical precision. In other words, Ivo understands your contracts as a lawyer does.
Legal teams—specifically those in the financial services and insurance industries—choose Ivo to enhance and standardize their agreement review workflows. Ivo’s use of bespoke playbooks promotes custom results with rapid, surgical redlines that accurately reflect an institution’s unique legal positions.
Want to learn more? See how Ivo can help you achieve similar results.
At Ivo’s inaugural customer advisory board (“Visionaries Board”) meeting, legal leaders from top companies, including Canva, Pinterest, Intel471, and others, came together to discuss the future of legal AI.
The conversation covered everything from risk management and redlining to speeding up contract review and rethinking how legal teams maximize their value.
What became clear? AI isn’t about replacing lawyers—it’s about reducing the time spent in the tedium of contract review to enable lawyers to spend more time focusing on strategic initiatives that drive business forward.
Here’s a look at the top takeaways from the Visionary Board’s first session and what it means for legal teams navigating the AI-laden path ahead.
The Visionaries Board emphasized that the goal behind implementing AI is not just efficiency, but the elimination of low-value work altogether.
One Visionary Board member specifically noted, "It’s not just about helping me do a task faster; I want to remove the task entirely."
Rather than manually reviewing every line of a contract, redlining a routine NDA, or triaging vendor forms, lawyers want AI to handle the full review and surface the provisions that pose the biggest risks or could impact strategic business outcomes. Some even imagine a future where traditional redlining fades away entirely, replaced by dynamic risk scoring that enables teams to act on priorities, not sift through edits.
A clause that scores 90% or higher on an acceptable risk framework? Route it to a junior reviewer. A liability cap significantly below the acceptable threshold? Escalate it to corporate counsel.
This shift in contract review processes could redefine how teams assess legal exposure and allocate time.
How lawyers use AI varies widely. Junior lawyers may default to over-redlining to capture every nuance or demonstrate competency, while seasoned attorneys may be more apt to accept low-risk deviations to their playbook to expedite deals.
That’s where AI can help–by providing junior lawyers with the same institutional knowledge as their experienced peers, embedded in a standardized playbook. The goal isn’t just speed, but alignment and clarity.
Context matters. Style matters. No two companies—or legal teams—approach risk the same way. That’s why customization is key.
Visionary Board members emphasized the importance of tailoring AI solutions to reflect how their organizations already operate, such as fallback clauses by product, risk profiles by team, or stylistic playbooks by user.
At its best, legal AI isn’t generic; it’s purpose-built to mirror your unique approach to contracts, risk, and business goals.
Visionary Board members also made it clear that the toughest part of legal transformation isn’t the adoption of the technology itself, but ensuring that it can co-exist with the judgment and reasoning that only legal teams and leaders can provide. Aligning stakeholders on definitions. Agreeing on risk thresholds. Positioning legal as a strategic partner, not a blocker.
AI can help support this shift by providing metrics, dashboards, and heat maps that highlight how legal contributes to efficiency, alignment, and risk mitigation—not just compliance.
But there are limits. Resoundingly, Visionary Board members agreed there are tasks AI shouldn’t do; it shouldn’t calibrate risk tolerance for business teams, navigate internal politics, or override human decisions. The role of AI is to enhance the legal team’s impact, not replace human judgment.
Whether you're exploring legal AI for the first time or scaling an existing implementation, here are five recommendations from the Visionaries Board to guide the way:
1. Start small, but smart. Focus on repetitive, low-risk tasks first, like NDAs or vendor reviews, and build trust with AI from there.
2. Codify your playbooks. The more clearly you define your preferred and fallback provisions and risk thresholds, the better AI can assist.
3. Invest in customization. Legal teams should control style, tone, and escalation logic, because risk isn’t one-size-fits-all.
4. Shift the metrics. Don’t just measure speed. Measure alignment with risk profiles, reduction in review cycles, and effectiveness.
5. Empower, don’t replace. Legal AI should enable attorneys to be more strategic, not take the human out of the loop. Think augmentation, not automation.
The Ivo Visionaries Board meeting highlighted how collaborative and forward-thinking our members are. These legal leaders aren’t just giving feedback; they’re shaping the future of legal AI. From model design to workflow integration, the Visionary Board members' insights directly influence how we build Ivo. As AI advances, expectations are shifting, too, and tools like Ivo are on track to evolve into peer-level teammates.
The consensus was clear – AI should surface what matters and never override human judgment. Legal teams want to spend their time focusing on strategic outcomes and assessing risks, not tracking changes line by line. We're grateful to our Visionaries Board for pushing us to build Ivo with clarity, context, and real-world impact in mind.
Connect with us now to learn how we can streamline your contract review process
.jpg)
