To keep sales context current for AI agents, connect the AI assistant (like Claude or ChatGPT) to a context layer it calls at question time instead of relying on training data or the CRM. Every claim should carry a date and a source link, refresh on a set cadence, and be corroborated before anyone acts on it.
Sales context is the information an AI agent or seller needs to decide which companies to work and why now: what each company is working on, the dated evidence behind it, and the people involved. It is current when the evidence is recent enough to act on and anyone can open the source to check it. Syft provides this as a context layer over MCP, so an AI assistant gets who to work and why now with dated evidence at the moment someone asks.
When Claude, ChatGPT, or another AI assistant gives outdated answers about a company, the cause is usually one of three things.
None of these are failures of the AI assistant. The model answers from what it has. The fix is to change what it has at the moment someone asks.
For GTM work, current context answers two questions with evidence:
Contact details and outreach come after those two answers. An agent with a perfect contact list and a stale reason will still send a message the buyer does not recognize. We cover how to tell a dated reason to act from a general company event in trigger events vs buying signals.
The most reliable pattern is an MCP context layer. MCP (Model Context Protocol) lets an AI assistant call an outside tool while it answers. Instead of guessing from training data or a cached page, the assistant asks the context layer which companies are working on a given problem and gets back the current list with evidence. We explain the setup in MCP for sales: how to give GTM AI agents real account context.
Every statement an agent might act on should carry the date of the evidence behind it, not the date it was retrieved. "Posted a role for this workflow on October 2" is usable. "Is hiring" is not. Dates let a person or an agent decide whether the reason is still worth acting on.
Decide how often each kind of evidence gets checked again. Fast-moving evidence like job posts and public writing needs frequent refreshes. Slower facts like company size or industry can refresh less often. Evidence past its window should drop out or be flagged rather than shown as current.
If a seller cannot open the source in about two minutes, they cannot verify it or use it in a message. Source links also let an AI assistant show its work, which is what earns trust from reps and managers.
One data point can be noise. A job post plus a leader writing about the same problem is stronger than either alone. Ask the context layer for corroboration, and treat single-source reasons as worth watching rather than worth acting on.
Use this to check whether your agents are working from current context:
If the answer to any of these is no, that is where stale data gets in. Building and maintaining this yourself is real work, as we cover in the GTM context pipeline: why it's hard to build and maintain.
Syft shows which companies are working on the problem you solve right now and why, with dated evidence and a source link for each reason. Contacts come after that, once the reason is clear.
Syft works through MCP inside the AI assistant your team already uses, including Claude, ChatGPT, and Cursor. That means:
For RevOps and GTM operators moving into GTM AI Ops, this replaces a lot of manual refresh work with one context source every agent and assistant can call. Better context in, better actions out.
In a custom demo, Syft runs on the problem you solve and shows the companies working on it now, with the dated evidence for each. You keep the results whether or not you buy. Book a custom demo.
Connect your AI assistant to a context layer through MCP so it pulls current evidence at question time. Make sure every claim carries the date of its evidence and a source link, refresh evidence on a set cadence, and corroborate reasons before acting.
Claude answers from its training data, which stops at a cutoff date, plus whatever it can find when it searches. Search results can be older pages, and CRM data it reads may have decayed. Giving Claude a context source through MCP lets it answer from current, dated evidence instead.
Require a date and a source on every claim the agent uses, drop or flag evidence past its refresh window, and have the agent call a context layer at question time rather than relying on stored records or memory.
It is a source of sales context that an AI assistant (like Claude or ChatGPT) can call through the Model Context Protocol while it works. It returns which companies to work and why now, with dated evidence, so the assistant does not have to guess.
It depends on the evidence. Job posts and public writing change quickly and need frequent checks. Firmographic facts change slowly. The key is that each claim shows its date, so anyone can see whether it is still recent enough to act on.
No. The CRM stays the record of your relationships and pipeline. Syft adds current, dated evidence about which companies are working on the problem you solve, available in your AI assistant through MCP.
