Your data is the lifeblood of your organization. So using anything but best practices to manage your data is a nonstarter. negotiagent typically uses cloud-based platforms to manage your data (upon request, we can also deploy our solution and manage your data on local servers). As part of the onboarding process, we set up a private and dedicated AWS, Azure or Google Cloud instance owned by you, whatever your preference. It's important for you to know where your data is at all times and how it's being used. We provide a fully managed service to remove any concerns or blockers related to cloud vendors. This allows our team to maintain the platform and software to the highest standards for security and compliance, as well as addressing zero-day issues centrally and effectively. Additionally, you own your data at all times. negotiagent will never claim ownership in any of your data.

Before LLMs and the rise of AI, many contract practitioners relied on contract Playbooks to provide drafting assistance. Playbooks are repositories of alternate, pre-approved contract clauses that can be used when a counterparty pushes back against your standard template provisions. Playbooks are typically manually updated and maintained in Excel files or tables in Word. Usually, Playbooks focus primarily on the big ticket contract provisions that are most heavily negotiated and not the whole contract. Playbooks are predicated on “if-then” logic and don’t capture interconnectivity of clauses. Playbooks don’t capture your full negotiation history or strategy. While Playbooks can be a useful analog tool to help with contract drafting, in the new AI world they are an imperfect starting point for training AI agents to automate contract negotiations. Consequently, negotiagent does not use contract Playbooks. Instead, negotiagent is designed around Acceptable Contract Range (ACR), a measurable goal that provides a range in which negotiagent can negotiate a contract on your behalf. Based on all your previous deals, Acceptable Contract Range captures every change you’ve ever made, in every contract provision. It examines every deal you’ve ever signed and measures how far you’ve deviated from your starting position, in every contract provision.

To replicate your individual negotiation and drafting style, it’s necessary to train the negotiagent solution on your specific contract data. We recommend a four-step process: Ingest and organize your contract data. Calculate your Acceptable Contract Range for each designated contract type (which gives the negotiagent a unique and measurable negotiation goal for each contract, tailored to what’s important for your organization). Identify your particular negotiation patterns so negotiagent understands your specific negotiation style, and which negotiation strategies you tend to deploy to reach the end game. Using our Word plug-in, we tie in the learnings from the previous steps to analyze a counterparty’s response to your starting template. negotiagent knows your organization’s objectives and risk appetite, and recommends strategic red lines that move the agreement towards your specific Acceptable Contract Range, all based on your negotiation patterns. After each phase, we work with you to make sure the results accurately reflect your real-world negotiations. An AI agent is only as good as the goals and tools you give it. See our Solutions page for additional information for each phase or schedule a demo via the button at the top of the nav. ​

Security is in our DNA. Safety and data security protocol are paramount. As a guiding development principle, we've established an internal talisman known as SERT, that governs how we design all our products. SERT requires any negotiagent solution to be: Secure Explainable Reliable & Transparent

negotiagent uses proprietary methods to analyze the moves you and your counterparty make during a contract negotiation. Having indexed every offer and counter-offer you’ve made in past negotiations, negotiagent identifies the most successful sequence of redlines that previously proved successful. negotiagent assesses the current negotiation and replicates tactics that strategically address the current negotiation. Like in a game of chess, you learn the most by analyzing the moves leading to checkmate.

Most contract Word plug-in solutions in the market all pretty much do the same thing. They compare incoming contract provisions against contract Playbooks, identify non-standard provisions, then insert discrete modular fall back provisions recommended by the Playbook. None of these Word plug-ins look at a contract as a whole or the relationship between clauses in an agreement. None of these products understand context or the actual negotiation goal. None think ahead over multiple negotiation rounds. All of these solutions are “co-pilots” that require the reviewer to decide whether suggested redlines make sense and rely solely on the reviewer to implement negotiation strategy. In essence, current Word plug-in offerings offer drafting suggestions, but can’t actually negotiate. This is where the negotiagent Word plug-in is drastically different. Like other Word plug-ins, negotiagent analyzes contract clauses, identifies non-standard provisions and makes drafting suggestions. But negotiagent takes this to the next level by making strategic negotiation suggestions with a purpose and always towards a measurable goal. So while every Word plug-in may look alike, the negotiagent Word plug-in uses a very different engine. Powered by AI agents that understand your negotiation patterns and style, the negotiagent Word plug-in makes a plan from the beginning, and provides strategic negotiation advice over multiple anticipated negotiation rounds – all towards a measurable negotiation goal.

Contract negotiations take way too long to finish. Most negotiations boil down to a handful of disputed points. But to get to these points, there are other, less contentious items that needlessly take up negotiation time. Negotiations drag on, and are completely inefficient. We want to automate how you negotiate. Using your contract history, negotiagent trains AI agents to replicate your negotiation patterns and strategies. negotiagent analyzes a counterparty’s response and makes strategic contract redlines that move the negotiation quicker to the end game.

How long it takes to implement the full negotiagent solution depends on the amount and types of underlying contract data. Because negotiagent is trained in your particular and distinctive negotiation patterns to replicate your style and strategy, our solution takes slightly longer to deploy than other legal tech solutions that rely on LLMs alone (but we continue to get faster). Our primary focus is to create a solution that is accurate, transparent and measurable (getting it right takes priority).

Here it is: the scary Terminator scenario question. No, negotiagent is not fully autonomous. And yes, you will still have a job (but will be able to do it quicker, more efficiently, and finally have time and headspace to do other, more important tasks after delegating the monotonous parts of negotiations to negotiagent). Full autonomy implies no outside input or oversight whatsoever. That’s never been our goal. Our goal is to train AI agents to automate contract negotiations, using your historical negotiation patterns to quickly negotiate contracts on your behalf, much faster and effectively than you could alone. There is always a human in the loop. Automating contract negotiations doesn’t mean contract negotiators are cut out of the process or have no control or oversight on how the negotiagent negotiates. Our solution is fully transparent and auditable, so you see all the moves the negotiagent makes, and the specific plan and steps it takes to reach your measured negotiation goal. (So no Skynet yet).

LLMs such as GPT, Claude and Llama have gotten really good at generating, summarizing and analyzing documents, but LLMs can’t really do anything for you or on your behalf. AI agents represent the next level of generative AI, where information leveraged from a LLM can actually be acted upon and used to carry out designated tasks. AI agents are given a goal, and use tools to plan, test and execute step-by-step solutions to achieve that goal. AI agents can be trained to reason through complex problems, create actionable plans and implement those plans using a suite of tools. In other words, AI agents can actually do something with data. A negotiagent is our specialized AI agent trained to replicate how you negotiate contracts. We have built a number of tools that our negotiagent uses to reach your specific contracting goals, as if you are handling the negotiation yourself. Based on your deal history, negotiagent is able to assess contract redlines, set a negotiation goal and make a plan to reach that goal by automating the necessary steps to complete the plan.

Yes. The privacy and security of your data is of utmost importance, and negotiagent adheres to GDPR requirements and other applicable data privacy rules and regulations. We follow best practices for EU regional requirements for data transfer, storage and processing. Privacy by design is an integral part of the negotiagent architecture.