Skip to main content
At any given point in time, there are 10,000+ active VCs globally that are writing checks into companies. For any given Company, there is only a very small subset of these VCs that are most relevant.
On the Metal platform, across 10,000+ raise processes, the single biggest point of failure lies in targeting VCs that are not “likely” partners for a given company. Specifically, our analysis shows that about 70% of all VCs that a founder targets are typically not a good fit for their Company’s specific stage, sector and business model.
On an ongoing basis, we see Consumer founders looking for a lead investor for Series A targeting racking up calls with investors that haven’t done a Consumer deal in years. We see B2B SaaS founders raising a pre-traction pre-seed round targeting seed-stage VCs that typically want to see clear signs of growth and product-market fit. Consultants can help founders avoid the above pitfall by using Metal’s advanced software capabilities to seamlessly and automatically identify the most likely investors.

​
Introduces the Investor Memory Layer

Metal’s platform is equipped with an investor memory layer that brings a deep understanding of each VC firm. Built on public signals, industry APIs and off-market intelligence, the investor memory layer interfaces with the user memory that Metal builds during the onboarding process for founders.
By putting together user and investor memory layers, Metal is able to identify the “most likely” investors for a given Company. The platform also provides deep visibility to founders on why a given investor is being ranked as a “Top 5%” fit, or a “Top 25% fit”.
Consultants can navigate through the UI to view the most likely investors, add these to a pipeline, and then have the in-app agent add brief notes on each investor to document the fit assessment. This entire process should take less than 30 minutes in total.