A warm-path tool finds who in your company's network can introduce a rep to a buyer, scores how strong each relationship is, and routes the ask through the right person. GTM engineers can build one in-house from Clay, a data warehouse and the CRM, or buy a platform that does it. This post covers what each route really involves, what in-house versions usually miss, and a checklist for deciding.
Why GTM engineers are building these now
Relationship data is the one input most GTM stacks lack, because no vendor sells who at your company knows your buyer. So the best GTM engineers have started building it themselves.
Lassie is a recent example. In a16z's announcement of Kyle Norton joining Lassie as CRO, Lassie's GTM engineer Michael Jin is described as having hacked together an internal tool that identified the most qualified customers and the warmest path to an intro. It has since been built into a platform the team calls Lighthouse, which ingests and prioritises thousands of leads and connects them into the team's outreach tools.
1mind went the other way. Its Head of Revenue Operations, Josh Carter, is a Clay power user who teaches AI in GTM, so building was the obvious first move. He scoped an AI relationship map in Clay and Salesforce covering investors, advisors and network overlaps, then dropped it and bought Boomerang AI. The 1mind case study lists what a real relationship graph needed:
- LinkedIn profiles re-scraped on a schedule
- Job histories tracked to find where people overlapped
- Engagement tracked across accounts
- A data warehouse to hold all of it
- A UI reps would actually use, which someone then has to maintain
"Now here I am managing a product when I should be doing more strategic work." Josh Carter, Head of Revenue Operations, 1mind
Both decisions were reasonable. The question is which one fits your team.
What an in-house version usually maps, and what it misses
Most first versions start from LinkedIn connections and CRM contacts. Sales Navigator's TeamLink is a good starting point here: it shows which colleagues are connected to a lead, and plenty of teams use it as their V1. The gaps tend to appear in the other networks and in everything that happens after a path is found:
| What a warm-path tool needs | Typical in-house first version | What a dedicated platform adds |
|---|---|---|
| Your team's connections | LinkedIn mutuals and CRM contacts | Calendars, email threads, call transcripts and Slack, scored for strength |
| Investors, advisors and board | A static list, matched by hand | Mapped against every target account, with the evidence for each path |
| Customer champions | Rarely included | Champions and their job moves, asked at the right moment |
| Partners | Rarely included | Partner relationships as a fourth network |
| Relationship strength | Whether a connection exists | How strong it is, how recent, and whether the person is willing to ask |
| Governance of asks | Nothing stops the same investor being asked five times | Limits each connector sets: deal size, channel, cadence and exceptions |
| Follow-up | Manual | Nudges when a connector goes quiet, then the next person on the chain |
| Where reps see it | A spreadsheet or a custom app | Slack, the CRM, and MCP for Claude and Codex |
| Upkeep | Re-scrapes, schema changes and UI fixes, forever | Maintained by the vendor |
The first row is where a build starts. The bottom five rows are where most of the ongoing work, and most of the value, sits.
The real cost is upkeep
A one-off scrape is a project. A relationship graph is a product: people change jobs, profiles change, new accounts get added, reps ask for features, and the person who built it becomes the person who maintains it. That was the turning point for 1mind. Before you build, count the hours per month the graph will need a year from now, not the weeks it takes to ship version one.
When building makes sense
- You have a dedicated GTM engineering team with time to maintain a product.
- Warm paths are one input inside a broader lead platform you are building anyway, as with Lassie's Lighthouse.
- Your relationship data is narrow and owned by you, for example one network such as your customers.
- You need a scoring model no vendor will support.
When buying makes sense
- RevOps or GTM engineering is one or two people with a long backlog.
- You want all four networks: executives and employees, investors and advisors, customer champions and partners.
- You need governance, so the same investor or board member is not asked too often.
- Reps need paths in Slack and the CRM this quarter, not after a build.
A decision checklist
- Which networks must the graph cover, and who owns each one?
- How will you measure relationship strength, and how often will you refresh it?
- Who maintains the scrapes, the warehouse and the UI in a year?
- How will asks be governed and followed up?
- Where will reps see paths: Slack, the CRM, an AI assistant?
- How will the outcome of each intro be logged so you can compare nearbound with other sources?
- Can you buy the graph and build your own workflows on top of it?
The middle path: buy the graph, build on top
Many GTM engineers end up here. 1mind runs a signals library in Clay and stacks it with Boomerang AI paths, so an account with several warm paths and a live need gets worked first, and the signals reach reps through Salesforce, Slack and Salesloft. Boomerang AI exposes paths through a REST API, webhooks and an MCP server for Claude and Codex, so the graph can feed whatever you build.
For more, see the GTM engineer playbook and our warm intro software comparison.
More questions
Can we buy the graph and still build on top of it?
Yes. Many GTM engineers buy the relationship graph and build their own workflows on it. Boomerang AI has a REST API and webhooks, and an MCP server for Claude and Codex, so paths can feed your scoring, Clay tables or outreach tools.
Frequently asked questions
Can I build a warm intro tool in Clay?
You can build a first version. Clay can pull LinkedIn connections, job histories and enrichment into a table and score overlaps. The harder parts come after: re-scraping profiles on a schedule, tracking engagement, storing it all in a warehouse, and maintaining a UI reps will use. That ongoing work is what led 1mind's RevOps lead to buy instead.
What data does a warm-path tool need?
At minimum: your target accounts and buying committees, the people on your side (employees, executives, investors, advisors, board members, customer champions and partners), and evidence of how well they know each target, such as past work overlap, shared boards, meetings, email threads and LinkedIn engagement.
How long does it take to set up a warm-path platform instead?
For Boomerang AI it is about 60 minutes of technical setup, the relationship graph builds in under a day, and full go-live takes about a week. LinkedIn and mailbox connections are optional.
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