Our teams perform best when the deal cycle is long, the product is technical, and the buyer is a VP or C-level who needs to be educated before they engage. We have done this for ten fraud and identity platforms, and for logistics, fintech, developer tools, and security companies selling into the same kind of committee.
We are not a fit for every business. The model works best for mid-stage and scaling B2B companies with an established product and a pipeline problem that hiring alone will not solve. When these six things are true, an embedded team compounds value year over year.
Technical buying committees are reached by multi-threading, not by volume. Every channel the team runs is pointed at every stakeholder who can say yes, and at the ones who can say no.
Our strongest engagements are in sectors where the product is complex, the buyer is technical, and the sales motion rewards domain knowledge over volume.
Transaction fraud, identity verification, bot mitigation, KYC and AML. We have built and run pipeline functions for more fraud and identity companies than any other category, from a two-rep start to an 18-person team, and our reps come in already fluent in risk scoring, false positive rates, and the compliance landscape their buyers live in.
Customs, freight, trade compliance, freight data. Multi-stakeholder buying processes with long evaluation cycles, prospected with native-language coverage across Latin America, EMEA, and North America.
Payments, equity management, compliance, tokenization, and financial data. Sales cycles involve technical evaluation, compliance review, and procurement. Our teams have sold into banks, payment processors, and financial institutions across multiple geographies.
Selling to engineering leaders means reps who can hold a technical conversation and qualify on fit, not just interest. Our teams have prospected for developer platforms, open-source compliance, and analytics infrastructure.
Selling security requires reps who can speak to threat models, compliance frameworks, and integration with the existing stack. Our teams have prospected into enterprise security buyers across endpoint, cloud, application, and API security.
Industry-specific platforms selling into defined buyer personas. This is where the embedded model shines: the TAM is finite, the accounts are known, and success depends on reps who learn the vertical deeply over time.
Selling AI and climate risk data into the enterprise means reaching leaders who evaluate on model performance, integration depth, and production readiness, often while the category is still being explained to them.
HR tech, legal tech, health data, learning platforms, cross-border e-commerce. If your product is technical, your ACV is high, and you sell to senior technical and operational buyers, the model applies. We evaluate fit on deal characteristics, not industry labels.
The same structural characteristics make an embedded team more effective than volume-based alternatives in every one of them.
Tell us about your product, your buyer, and your market. We will tell you whether the model is the right fit and how we would structure the engagement.
Book a scoping callNo long-term contract required. Start with one role and expand from there.