ROC Earns #1 Global Ranking in NIST ELFT Latent Fingerprint Benchmark, Strengthening Its Position in Mission-Critical Identity Security
Rhea-AI Summary
ROC (Nasdaq: ROC) announced a #1 ranking in the NIST Evaluation of Latent Fingerprint Technologies (ELFT) using the DoD-provided dataset, achieving the lowest False Negative Identification Rate (FNIR) at Rank-11 and top Rank-1 accuracy on the 5,259 latent-probe benchmark.
ROC also reported the fastest search speeds and smallest template size, positioning its unified Vision AI platform as efficient for large-scale ABIS, law enforcement, and defense deployments while supporting recurring revenue potential and attractive margins.
Positive
- #1 ranking in NIST ELFT on DoD-provided dataset
- Lowest FNIR at Rank-11 on a 5,259-probe benchmark
- Highest Rank-1 accuracy reported among evaluated vendors
- Fastest search speeds and smallest template size improving efficiency
Negative
- None.
News Market Reaction – ROC
In the Mar 2 session, ROC declined 6.15%, reflecting a notable negative market reaction. Our momentum scanner triggered 3 alerts that day, indicating moderate trading interest and price volatility.
Data tracked by StockTitan Argus on the day of publication.
Key Figures
Historical Context
| Date | Event | Sentiment | 24h Move | Catalyst |
|---|---|---|---|---|
| Feb 23 | Upsized IPO closing | Positive | +9.4% | Closing of upsized IPO with $24M gross proceeds and Nasdaq listing. |
24h Move is the share-price change in the day after each event; other market factors may also have contributed.
The only prior event, the upsized IPO, saw a positive price reaction, indicating early sensitivity to favorable corporate developments.
In the past weeks, ROC completed an upsized IPO of 4,000,000 shares at $6.00, raising $24.0 million in gross proceeds and beginning trading on the Nasdaq Capital Market on Feb 20, 2026. That event produced a 9.43% 24-hour gain. Today’s NIST ELFT #1 ranking continues a narrative of early commercial and technical validation shortly after listing, reinforcing ROC’s positioning in mission-critical identity security.
Key Terms
false negative identification rate (fnir) technical
latent fingerprint medical
AI-generated analysis. How Rhea-AI works. Not financial advice.
ROC delivers top Rank-1 accuracy and search speed on the DoD-provided dataset, supporting high-confidence searches at scale
Next-gen efficiency reduces infrastructure demands and total cost of ownership for real-world deployments by law enforcement, intelligence, and ABIS operators
DENVER, CO, March 02, 2026 (GLOBE NEWSWIRE) -- Rank One Computing Corporation d/b/a ROC, (Nasdaq: ROC) (“ROC” or the “Company”), a U.S. leader in multimodal Vision AI, building sovereign biometric, video analytics, and mission intelligence solutions into a unified platform, announces its latent fingerprint algorithm has been ranked #1 in performance with the lowest False Negative Identification Rate (FNIR) at Rank-11 on the U.S. Department of Defense (DoD)-provided dataset, the largest dataset in the latest National Institute of Standards and Technology (NIST) Evaluation of Latent Fingerprint Technologies (ELFT). These results reinforce ROC’s ability to deliver reliable identity verification in high-throughput, mission-critical environments.
“Latent fingerprint identification is one of the most challenging problems in biometrics. Achieving the lowest FNIR at Rank-1 on the largest dataset in ELFT reflects years of focused algorithmic innovation. Our goal is not just to perform well in controlled settings, but to deliver consistent, high-confidence matching under real operational conditions,” said Dr. Joshua Engelsma, Principal Scientist at ROC.
NIST’s largest latent fingerprint benchmark uses the DoD-provided dataset, comprised of 5,259 latent probes. In this context, ROC’s algorithms outperformed industry constituents delivering the highest Rank-1 accuracy, fastest search speeds, and smallest template size. This performance, combined with strong search efficiency relative to legacy technology providers, underscores the Company’s competitive positioning in large-scale, mission-critical ABIS deployments and next-generation identity programs.
NIST benchmarks are widely referenced in federal, defense, and international agency vendor evaluations. ELFT rankings provide a transparent, standardized basis for comparing competing critical identity and intelligence technologies. ROC’s unified Vision AI platform presents a significant competitive advantage by delivering cross-operational value to the end customer through efficiency gains, while supporting durable recurring revenue and attractive margins for the Company at scale.
"Performance at scale demands more than just accuracy; it requires a critical balance of precision and efficiency. Our algorithms are optimized to deliver consistent, low-latency performance even across millions of records," commented Keyur Patel, ROC’s Director of Machine Learning.
The NIST ELFT program is widely regarded as the most rigorous independent benchmark for latent fingerprint matching and serves as a key reference point in agency evaluation and procurement processes worldwide.
Read ROC’s Blog Post and Full NIST Scores here.
About ROC
ROC is a leading U.S. developer and manufacturer of Vision AI, delivering sovereign biometrics, video analytics, and mission intelligence through a unified platform. This enables agency and integrator partners to unlock faster, more accurate, and cost-efficient capabilities. At its core, ROC transforms raw pixels into real-time operational awareness for defense, public safety, and digital commerce. The Company is headquartered in Denver, Colo., with additional hubs in Grand Rapids, Mich., and Morgantown, W.V. For more information, please visit the Company’s website: www.roc.ai.
Media inquiries:
Matt Aitken, VP of Marketing
media@roc.ai
Investor inquiries:
CORE IR
ir@roc.ai
1 Rank-1 identification rate is what percentage of queries had their mate at the first retrieval rank (i.e., the closest match or in other words, the candidate with the highest similarity score to the probe image out of the entire gallery of candidates). Source: https://fiswg.org/
