Syft AI

B2B sales teams and reps believe they are working the right accounts, but most addressable revenue is invisible to them. The buyers who would purchase today never come inbound, never fill out a form, and never land on a territory list, so reps waste time on static lists and cold outreach built on invented personas rather than real evidence. GTM AI agents and sequencers face the same issue: when given thin context, they invent personalization instead of working from a verified reason to engage. Intent data and lookalike models help with timing or market sizing but still leave the seller or the agent to guess the actual reason a company would buy.

Syft AI scans a company's own website to learn its specific value propositions and win stories, then uses that as a basis to search for accounts in the market showing public evidence of an active, matching problem, such as hiring patterns, leadership changes, structural events, exec commentary, or technical documentation with dates attached. It returns a list of 'Value Matches': specific companies paired with a checkable reason to engage, dated evidence, and signals about who to contact, rather than a score or a bigger list. The product exposes this context over MCP so it can feed agentic tools like Claude, Grok Bot, or Codex, or be worked directly by sales reps, while execution (sending, sequencing, follow-up) stays in the tools a team already uses. Onboarding involves Syft building a profile from what the company sells, granting access including MCP, and reviewing the first batch of matched accounts on an initial call.