Introducing Unify's Infinity Signal
We’ve found that every business has unique signals that indicate when and how to engage potential buyers. These signals evolve constantly as products, markets, and competitive landscapes shift. No amount of static data enrichment can fully capture this complexity.
The best sellers already do this work manually—tracking competitor mentions, using AI search engines, digging into financial filings, and more. But this process is slow, inconsistent, and difficult to scale. With AI Agents, we can now do this research at a new level of scale and speed.
How the Infinity Signal solves the problem
We needed a system that could replicate and scale the research process of top sellers - one that could constantly search for relevant triggers and connect the dots. We’ve developed the Infinity Signal, an AI driven approach to continuously monitor your market to capture the most critical buying signals and take action based upon them.
Research agents needed toolkits that could answer complex questions with precision. From scraping websites, ingesting the latest news, leveraging AI search engines, and fetching social media activity, agents have an extensive set of tools and can determine the best ones to use to deliver the right answers.
To make sure that these agents were repeatable and reliable, we introduced a structured process using LangChain. The AI agent builds a research plan, searches and collects relevant data, and then reflects on its findings before providing answers. We have partnered with OpenAI to use frontier models like o1, which excels at step-by-step planning, to help our agents think critically about each signal they are researching. We’ve made o1’s thinking process transparent to users, to make sure you can reproduce and diagnose how conclusions were reached.
Scaling these agents was another challenge. The agents needed to be able to handle a variety of customer use cases with high fidelity. To achieve this we built a number of evals to assess performance on a range of core tasks. As we change the architecture, try new models, and add new tools, this enables us to track the output quality and benchmark changes.
Research alone doesn’t drive revenue, action does
Surfacing information without a clear way to use it would create yet another bottleneck. Sellers use the datapoints they collect to tailor outreach, so we built AI that could do the same.
The bridge between research and action is Smart Snippets, which uses LLMs to generate partial email copy that is highly relevant and contextual. We believe that humans hold unique context on the nuances and value of their business, and can create sequences by interweaving smart snippets with their own voice and touch. The result is scalable messaging that still feels human and relevant.
For example, an AI infra company can look for signals of product built on certain LLMs in Github activity, docs, or the news and then use those pieces of research to write messaging that references these signals in detail.
AI Agents now allow teams to multiply your best sellers by powering deep research and relevant action. This level of scale, repeatability, and customization gives businesses a competitive advantage in reaching their market and the Infinity Signal will enable customers to grow with unprecedented precision and velocity.