Scaling contract work by staying intentionally small
How a focused, user-centric contract co-pilot helped a lean team move faster on everyday work.
đ Hey there, Iâm Hadassah. Each week, I unpack how in-house legal teams use AI to enable the business, protect against risk, and free up time for the work they enjoy mostâwhat works, what doesnât, and the quick wins that make all the difference.
Before we dive in, a quick note: this is just one example of a legal team solving an operational bottleneck. There are plenty of ways to approach these kinds of problems, and the right solution will always depend on your specific needs and context. My goal is to give you some food for thought as you define what that solution should be.
Problem
Joining us is the Head of Legal at a fast growing FinTech startup. Their small team found itself under growing pressure as demand from across the business steadily increased, while capacity remained tightly constrained. What began as a three-person team was soon reduced to two, leaving fewer hands to manage the same volume of work. Most requests centred on reviewing and drafting agreements, extracting key data from contracts, and conducting legal research. None of this work was particularly novel or complex, but it was time-consuming.
The challenge was compounded by the nature of the business they supported. Many counterparties were large financial institutions with significant leverage, often insisting on using their own contract templates. Each agreement required careful review, often across multiple jurisdictions and languages. The work added up quickly. Routine contract analysis and data gathering consumed time that senior lawyers would rather spend on higher-value advisory work. Without a way to scale their efforts, the team risked becoming a bottleneck.
Solution
The team tackled this challenge head-on, first mapping their current bottlenecks and defining what success looked like to them:
faster contract reviews and data gathering;
natural language interaction capabilities; and
multi-lingual/multi-jurisdictional support.
To find the solution that fit these requirements, the team focused on understanding what the market could realistically deliver and how tools performed in practice. Many solutions promised relief but fell short: some were built for enterprise-scale transformation, others were slow, clunky, weighted down by poor UX, designed for far broader use cases than they needed, or priced beyond what made sense for their first real technology investment.
What the team needed was sharper. Not a platform that tried to do everything, but a practical legal co-pilot that could accelerate everyday work without heavy implementation or risk.
Speed to value was their guiding principle. The team wanted something that could help immediately, without months of configuration, integrations, or organisational change. They werenât optimising for automation for its own sake, but for real acceleration of high-volume work. For this, they needed a tool that could act as a sounding board, surface relevant information quickly, and reduce friction in first-pass reviews.
After demoing roughly half a dozen tools over several months, the team selected Robin AI (acquired by Scissero) as their legal co-pilot. It stood out for its intuitive, responsive UX and its ability to support natural-language interaction directly within documents. Just as importantly, it was right-sized. It wasnât a CLM or a comprehensive research platform, but a focused tool designed to support daily legal work.
Letâs dig a little deeper: From a technical perspective, the setup was intentionally simple. Robin AI was deployed as a Word plugin, with optional access via a web portal. There were no integrations, no onboarding programs, and no custom infrastructure. The low cost and low risk made the decision straightforward, enabling the team to move forward quickly without lengthy procurement cycles or heavy stakeholder management.
Results
The legal team reduced the time spent on first-pass contract reviews and routine data extraction, allowing lawyers to work faster and focus on higher-value tasks.
Team members reported increased confidence in early-stage reviews and drafting communications after testing the tool on real-world scenarios.
The low-cost, plug-and-play setup enabled fast experimentation without long-term commitment or organisational disruption.
Process
The initiative was owned entirely by the legal team, which simplified alignment from the outset. Because stakeholders were already embedded in the problem space, buy-in came naturally. The team needed faster redlining and clearer contract insight, along with support for research and review. Everyone stood to gain, which kept decision-making focused and pragmatic.
Instead of locking themselves into an exhaustive requirements list, the team chose to learn by doing. Over a three-month period, they demoed shortlisted tools using non-sensitive documents that closely mirrored live agreements. This âlive fireâ testing approach helped distinguish polished sales demos from tools that could perform under real-world conditions and surface practical use cases organically.
Budget discipline played a decisive role. A modest budget avoided prolonged procurement and reduced the risk of failure, acting as a forcing function away from over-engineered platforms. When Robin AI emerged as a strong candidate, its low cost and simplicity reinforced the decision. The downside of trying it was minimal, while the potential upside was immediate.
Implementation was straightforward. With no integration or onboarding required, the tool went live immediately. There were no formal training sessions; instead, the team validated outputs through hands-on testing with dummy agreements, building confidence through use. Not every tool the team had tested met their expectations, and early disappointments sharpened the teamâs focus on UX as a non-negotiable. The lesson was clear: even powerful functionality fails if lawyers donât want to use it.
Quick Wins
Looking beyond features, the team tackled their capacity constraints by clearly defining success, prioritising ease of implementation and usability, and learning by doing to cut through the noise. The quick wins that helped them build momentum and keep the project moving were:
Keeping scope intentionally narrow. By resisting the temptation to adopt a solution with broader use cases, the team was able to focus on scaling a single, high-volume task: faster interaction with contracts. This clarity made the benefits obvious and avoided the confusion that often slows adoption.
Testing with dummy agreements. Before relying on the tool in live matters, the team ran non-sensitive contracts through the system to validate accuracy and understand limitations. This built trust quickly and avoided surprises.
Prioritising UX over feature depth. By choosing a tool that felt intuitive from day one, the team removed one of the biggest barriers to adoption and ensured the solution fit naturally into daily work.
Involving the whole team early. The team participated in demos and testing, which surfaced real use cases and created shared ownership of the decision.
Focusing on acceleration, not perfection. The team treated the tool as a starting point and accelerator, not a replacement for legal judgment, which set realistic expectations and encouraged practical use.
Now itâs your turn. If your team is dealing with something similar, I hope this story sparks a few practical ideas you can put to work.
And⊠if youâve been through something similarâor solved a different operational challenge altogetherâIâd love to hear your story and spotlight your win.