The GTM Engineer bridge.
Norm Ai closed the $50M Series C with Blackstone in November. Without a RevOps hire in seat, the pattern I see at regulated-vertical AI companies: demand gen scoring and routing live in spreadsheets while the pipeline scales. Concretely tied to my AssetWatch delivery model (custom GPT giving leadership natural-language access to production Salesforce, 4 weeks): ship the system, document it, hand it back. I run the GTM Engineer function so the layer under your campaigns gets built now.
Demand gen at a Series C compliance company is capped by the infrastructure underneath.
You can run a clean campaign, hit the right CCO and Legal personas, and generate qualified inbound. If SFDC routing sends those leads to the wrong rep or scores a Legal contact the same as a CCO, the campaign that worked looks like it did not. At a Series C compliance ICP, every demand-gen dollar deserves a path to pipeline that does not depend on a rep eyeballing a spreadsheet. The fix is the scoring and routing layer your RevOps hire eventually owns. I build it while you hire.
Three things only an internal builder can fix.
Spreadsheet scoring ages out the day you ship it
If ICP scoring lives in Google Sheets and gets re-uploaded weekly, the model lags every new product launch and every new buyer pattern. Your highest-fit inbound gets the same treatment as a generic dev-tools lead.
Committee buyers need persona-aware routing
A CCO downloading a compliance whitepaper and a Legal lead hitting a demo request are different stages of the same cycle. If routing does not know the difference, both get the same AE follow-up and the better signal gets wasted.
Demand reporting only as honest as the funnel underneath
Without enforced stage definitions and clean account fields, campaign attribution rolls up to a blended number that hides which channel is actually working. Budget conversations get harder than they need to be.
A demand-gen infrastructure layer that turns every campaign dollar into a real path to pipeline.
- Weeks 1 to 2
Build ICP scoring from Norm Ai compliance-buyer signals
Audit current scoring, persona definitions, and routing rules. Build a real scoring model that distinguishes CCO, Legal, and RevOps signals. Same delivery model I ran at AssetWatch in 4 weeks, tuned here for demand gen instead of leadership query access.
- Weeks 3 to 4
Wire SFDC routing and nurture sequences
Inbound demand reaches the right rep automatically. Persona-aware nurture tracks fire on the right signal for the right buyer. Campaign attribution reads from a funnel you can defend.
Salesforce in plain English, shipped in 4 weeks.
AssetWatch leadership wanted natural-language access to pipeline, accounts, demo outcomes, and work orders without filing a RevOps ticket for every question. I shipped a custom GPT in ChatGPT Enterprise that translates English to SOQL and queries production Salesforce live. Two Knowledge files made it work: an auto-generated schema catalog covering 26 objects and 3,800+ fields, plus a hand-curated semantic layer encoding AssetWatch tribal knowledge, so "who owns this deal" returns the Solution Architect and "deal size" returns ARR, not the raw admin fields. Read-only, leadership-facing, 4 weeks. Tyler's team owns the maintenance now.
Same play I would run for Norm Ai. Different stack, same fixed-fee discipline.
$15,000, fixed. 6 weeks. One invoice.
- Signal architecture
- Account list and buying-committee map
- Sequence build, live send, and deliverability infrastructure
Documentation and handoff included, not billed. If volume justifies it after the bridge, $25,000 / 90-day retainer extends the system. Your call, not mine.
Reply if this maps to where you are.
Send me a sentence on how the pipeline reads today, and I will reply within a day with a 1-page scope and an honest read on whether this fits.