The founders of Darcy Partners have spent the last decade working in and with O&G companies, finding and investing in innovative technology companies. Darcy also recruits the top subject matter experts within each topic to contribute to the research and scouting exercise. These experts participate in the quarterly forum.
We classify our datasets into an Oil & Gas specific taxonomy that does not exist with generalist data service providers. We realize that datasets of 100s of startups require clear a classification methodology that is built for – and easily used by – insiders.
Our data subscriptions are evergreen, updated on a regular basis, and at the finger tips of our clients.
We maintain a robust database of emerging companies for each coverage area. Our data subscriptions allow our clients to visualize white space and vendor groupings within a taxonomy based on Oil & Gas.
We maintain an exclusive corporate forum of industry players that meets on a regular basis to set technology priorities for research and scouting and collaborate on the results of our findings. The forum convenes quarterly (in person) to collaborate and evaluate live presentations from our top hand selected startups.
Those companies that focus solely on internal innovation will miss out on the opportunities available externally. As Bill Joy, founder of Sun Microsystems once declared, “no matter who you are, most of the smartest people don’t work for you.
Time and time again we see the industry quietly iterate on tens of pilot projects with competing emerging companies until it becomes clear as to who can deliver the most value. This leads to the spread of misinformation and slow adoption cycles from so much vendor deluge. The forum is intended to quickly bring together a level of transparency to the industry that simply does not exist anywhere else.
Corporate and Institutional Investment firms are limited to costly options when it comes to targeted deal sourcing and validation. The forum provides the benefits of trusted research, deal flow and validation at an order of magnitude less than the next best option.