Insights, stories, and innovations from the team building AI for defense, infrastructure, and federal contracting.
How a terrain intelligence company accidentally built an AI tool for federal contracting
We built GovRanker out of frustration. After winning a SBIR Phase 1 with the U.S. Air Force, we were spending 5–8 hours a week just searching SAM.gov for the next opportunity. So we built an AI that does it in 15 minutes — scanning, scoring, ranking, and reading every attachment so you don't have to.
Exploring how distributed AI architectures tackle complex, real-world defense and industrial problems.
How GeoGizmodo deploys machine learning in environments where connectivity and compute are limited.
The full story of how we went from a technology concept to winning a U.S. Air Force Phase 1 award.
Our AI-driven predictive maintenance solutions are now available on the DoD CDAO TradewindAI platform — connecting us directly with government agencies and defense stakeholders.
Alex Zare, M.S., AI & Full Stack Engineer at GeoGizmodo, speaks on how AI is revolutionizing predictive maintenance and giving teams unprecedented visibility into equipment health.
How FracAdapt's physics-informed AI prevents ecological damage at hydroelectric dams by predicting turbine failures 36 hours in advance.
© 2026 GeoGizmodo LLC | All Rights Reserved
Patent Pending | SBIR Phase 1 Award Winner
¹ Performance claims are based on internal testing and early SBIR Phase 1 data. Actual results may vary and are not guaranteed.
² Patent-pending status refers to a U.S. Provisional Application filed March 2026. Issuance is not guaranteed.
How a terrain intelligence company accidentally built an AI tool for federal contracting
By Aneesh Hariharan, Founder — GeoGizmodo & GovRanker
Last year, my team at GeoGizmodo won a SBIR Phase 1 with the U.S. Air Force. We build predictive maintenance and terrain intelligence systems using machine learning. It was a huge milestone for us as a small business.
Then came the hard part: finding the next opportunity.
If you've ever tried to find federal contracts on SAM.gov, you know the drill. You log in, run a search, get 400 results. Half are expired. A quarter don't match your NAICS code. The rest require you to download a 47-page SOW just to figure out if it's even worth your time.
We were spending 5–8 hours a week just looking for opportunities. Not writing proposals. Not doing technical work. Just searching, filtering, reading, and deciding "nope, not a fit." For a small team, that's brutal.
One night I was reading through my third SOW of the evening — a 60-page document for what turned out to be a janitorial services contract that had nothing to do with us. It showed up in our search because it mentioned "predictive maintenance" once in the context of HVAC systems.
That was the moment I thought: we literally build AI systems for a living. Why are we doing this manually?
What started as an internal tool quickly became something bigger. We called it GovRanker. The idea was simple: what if an AI could do what we were doing manually, but in minutes instead of hours?
The AI reads your site, understands your capabilities, identifies your NAICS codes, and builds a profile of what you're good at.
Every new opportunity gets pulled in automatically. No more manual searching.
NAICS alignment, keyword relevance, set-aside eligibility, agency fit, deadline urgency, and more. You get the 20 that actually matter, ranked by fit.
SOWs, amendments, RFPs, pricing sheets. The AI downloads and reads them all so you don't have to open a single PDF.
With reasoning — not just a score, but an explanation of why something is or isn't a fit.
Technical volume and cost volume structure, ready for you to build on.
Nothing and everything. GeoGizmodo's core is geospatial AI and predictive analytics. We process satellite imagery, build ML models for terrain classification, and predict equipment failures for military vehicles. But the skills that let us build those systems — processing large datasets, building scoring algorithms, training models to find patterns in noise — are exactly what you need to solve the SAM.gov problem. Federal opportunity data is just another dataset. Matching companies to contracts is just another classification problem.
This is our first product launch. It came from our own pain, built with the same AI capabilities we use for defense work.
Searching for opportunities — Down from 5–8 hrs/week
Missed opportunities identified — In the first month
Increase in proposals submitted
We built this for ourselves, but we realized every small business doing federal work has the same problem. The big primes have dedicated BD teams with 10 people scanning SAM.gov all day. Small businesses have one person doing it between actual project work. That's not a fair fight. We think AI can level it.
If your team spends too much time on SAM.gov and not enough time writing winning proposals, give it a look. Enter your company URL, let the AI do its thing, and see what it finds.
Two free searches, no credit card required.

Aneesh Hariharan is the founder of GeoGizmodo, a terrain intelligence and predictive analytics company, and GovRanker, an AI-powered federal opportunity discovery tool.
LinkedIn Profile | hello@geogizmodo.ai
How FracAdapt's physics-informed AI prevents ecological damage at hydroelectric dams
By the GeoGizmodo Editorial Team
In the rugged heart of the North Cascades, Ross Dam stands as a monument to engineering and a primary source of clean energy for the Pacific Northwest. But beneath the hum of its massive turbines lies a delicate ecological balance.
Most people assume the danger to salmon at dams is the physical barrier itself. However, downstream from Ross Dam, a more invisible threat exists: Downramping. When a turbine bearing spikes in heat or a blade vibrates out of tolerance, the system triggers a 'Hard Stop.' The river level downstream crashes within minutes, leaving juvenile fry stranded and nests dewatered — mortality events that can decimate an entire generation of salmon.
This is where FracAdapt, GeoGizmodo's flagship AI platform, changes the narrative. Built on a foundation of physics-informed AI and validated by SBIR defense awards, FracAdapt moves the needle from 'reacting to failure' to 'foreseeing it.'
FracAdapt doesn't wait for a sensor to hit a 'danger zone.' Our physics engine crunches real-time data from existing SCADA probes, using material science and degradation models to 'sniff out' anomalies like blade shear or bearing fatigue thirty-six hours before they trigger a shutdown.
When FracAdapt identifies a risk, its AI Agentcores go to work. Instead of a simple alarm, the system drafts a 'Proactive Transition Plan.' It calculates the exact rate to ramp up auxiliary spillways to compensate for the failing unit, ensuring that the river's pulse never skips a beat.
The system can even auto-schedule drone fly-bys to monitor the downstream reach, providing operators with high-definition visual confirmation that water levels are remaining within the strict 1-inch-per-hour federal safety limits.
FracAdapt identifies risks before they trigger shutdowns
Preventing flow crashes that kill salmon populations
Planned repairs instead of emergency shutdowns
By implementing FracAdapt, critical infrastructure becomes a partner to the environment, not an adversary. We prevent the 'Flow Crash' that kills fish, catch erosion early for planned repairs instead of million-dollar emergencies, and protect utilities from massive fines associated with dewatering events.
At GeoGizmodo, we aren't just saving machinery; we are protecting a legacy. The salmon of the Skagit River have enough hurdles to clear — a mechanical glitch shouldn't be one of them. Through the power of Physics-Informed AI, we are ensuring that the North Cascades remain powered, and its rivers remain full of life.
This article was written by the GeoGizmodo Editorial Team. GeoGizmodo builds physics-informed AI and predictive analytics systems for defense, infrastructure, and environmental applications.
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