Short answer: To find companies that need your product right now, look for dated evidence that a company is actively working on the problem you solve. Write the problem in buyer language, list what a company does in public when it has it, search for that evidence with dates, rank by strength and recency, and check your CRM. Syft AI finds that evidence and delivers who to engage and why now, with a dated source behind each company.
This post gives a short version of the method and a neutral comparison of tool categories. For a related post with the full method, see How to Find Accounts Ready to Buy: A 6-Step Method.
Fit shows who could buy, and evidence shows who needs it now. A customer profile narrows the field by industry, size, region, and tech stack. Thousands of companies can fit on paper, and only a small share of them are dealing with your problem this quarter.
Need shows up as activity. A company that needs your product is usually already doing something about the problem: hiring for it, budgeting for it, talking about it, or building around it. That activity is what separates a company that could buy from one with a reason to talk now. We explain the distinction in more depth in The Difference Between Account Fit and Buying Timing.
A five-step method turns public evidence into a ranked list of companies, each with a dated reason. Steps 1 to 4 are summarized below. For the full method, see the related post How to Find Accounts Ready to Buy.
Product pages describe solutions, and buyers describe problems. Write the problem the way a buyer would say it internally, because job posts and announcements use that language. "We cannot keep up with compliance reviews as we expand into new regions" is easier to search for than "automated compliance platform."
List the public actions a company takes when it has the problem, because those actions can be searched, dated, and checked: hiring for it, launching an initiative, changing leadership, expanding into new markets, or talking about it in public.
Collect each piece of evidence with the date it appeared and a link to the source. Recent evidence says more about need today, and a source lets a seller check the reason before using it.
Not all evidence is equal. Rank companies higher when the evidence names your problem directly, several pieces point the same way, the evidence is recent, and the company fits your customer profile.
Before anyone reaches out, check your CRM for open deals, recent closed-lost reasons, and prior conversations with the company. First-party history keeps a good reason from turning into a bad touch, and closed-won patterns show which evidence led to revenue before.
The strongest evidence has three qualities: it is specific to your problem, it is dated, and it is verifiable. A few examples of how that looks:
Weaker evidence is generic, old, or hard to check. Broad research topics, years-old funding rounds, or a tool listed on a website with no date attached tell you little about need today. For a fuller list of evidence types, see What Are Go-To-Market Signals. For a related post on building outreach around these signs, see Building an Outbound Strategy Around Problem Symptoms.
Each tool category answers a different question, and most teams combine several. Here is what each category answers and when it works best.
Your CRM and call notes sit alongside all four and hold first-party history on every company you have touched. For companies that intent tools miss, see the related post How to Identify Unlisted In-Market Accounts. A useful test for any category is whether it shows which companies have your problem now, the evidence behind that view, and a source you can check.
Finding the right companies pays off when someone acts on them. Lists stall when research covers the top accounts and the rest wait.
Sellers can use their AI assistant (like Claude or ChatGPT) to prep for a call or draft a reply in the moment, while agents handle repeatable background work: researching every prioritized account, drafting first touches from the evidence, and watching for new evidence. Sellers get their research time back and spend it on conversations.
Teams that attach a dated reason to every prioritized account can measure three targets over their first 30 days: every prioritized account acted on, new pipeline from evidence-led outreach, and a second-meeting rate above their current baseline. See GTM AI Metrics That Matter in the First 30 Days.
Syft finds companies showing evidence of the problems you solve, identifies who to engage, and explains why now, with dated, sourced evidence behind each one. Claude calls Syft through MCP, so the evidence shows up where your team already works, alongside your CRM.
Describe the problem you solve in buyer language, list the public actions a company takes when it has that problem, search for those actions with dates and sources, rank companies by strength and recency, and check your CRM before reaching out.
Look for dated evidence that the company is already working on the problem, such as job postings, new initiatives, or leadership hires in the area. Fit shows who could buy, and activity shows current need.
Most teams combine a data provider for fit and contacts, their CRM for history, and a source of dated problem evidence. Evidence and why-now platforms like Syft focus on that last part, and Syft delivers it to Claude through MCP.
No. Intent data shows topic-level interest, and a seller still needs a specific, dated reason they can verify.
Evidence from the last few weeks is stronger than evidence from last year, so refresh prioritized accounts continuously.
Yes, when it has current, sourced evidence to work from. Connecting it to a context tool through MCP gives it that evidence, and its answers then rest on fresh sources.
Syft finds companies with evidence of the problems you solve, with a dated source behind each one, and delivers them into the AI assistant your team already uses. Book a custom demo to see your own prioritized accounts.
Better context in, better actions out.
