Deploying cutting-edge AI capability to the tactical edge doesn’t matter if the data pipeline can't be trusted. At the GEOINT 2026 Symposium, Project Geospatial sat down with Rich Cinquegrana, Senior AI/ML Engineer at TekSynap, to talk about the company's internal R&D efforts and engineering philosophy.

In this blog post, we look at how TekSynap uses Model-Based Systems Engineering (MBSE) to completely eliminate bloated paper trails, replacing them with object-oriented software designs that make system dependencies clear. Pulling from his extensive history with the NGA's Project Maven, Rich shares how TekSynap’s TechAccelerate Lab sandbox and Foundry are engineering secure AI pipelines that block adversarial spoofing, ensuring a trusted chain of custody from initial imagery capture to finished intelligence report—all while aligning capability directly to cost to preserve vital taxpayer value.