explainable AI

Aruspex Inc. delivers zero-knowledge verification for AI and computational systems, proving AI correctness without exposing models, data, or code. Its ZKML framework generates cryptographic proofs that AI predictions meet specified accuracy or safety thresholds, verifiable by third parties. Applications span defense, space, autonomous systems, and quantum computing benchmarking. Founded in 2023 by Emily Wan.

AI inference verificationcryptographic validationquantum benchmarkingzero-knowledge proofsZKML verification

BullFrog AI Holdings, Inc. (NASDAQ: BFRG) uses explainable AI and machine learning to accelerate drug discovery and development for biopharma teams. Its platform combines biology-aware data harmonization, Causal AI analytics, and structured, auditable decision support to turn multi-omic and clinical data into patient subgroups, translational signals, and candidate rankings. bfLEAP® was developed in partnership with Johns Hopkins University Applied Physics Laboratory, and its neuroscience data infrastructure is built with the Lieber Institute for Brain De

Causal AI analyticsdata harmonizationdecision supportdrug target discoverymachine learningpatient stratificationpatient subgroup discovery

Compsim is headquartered in Brookfield, Wisconsin. It develops KEEL (Knowledge Enhanced Electronic Logic) Technology, which puts human-like decision-making and reasoning into products or software applications. The KEEL Toolkit lets a domain expert model decision-making processes and translates the graphical model into conventional code for integration into devices, software, or the web.

analog circuit implementation of cognitive modelscode generationdata fusiondecision-making modeling

digiLab is a pioneering AI company that empowers governments and organisations in safety-critical or highly regulated industries to solve critical, complex, and high-stakes challenges using machine learning and uncertainty quantification. Its trustworthy and explainable AI platform, the Uncertainty Engine, is supported by a team of machine learning specialists and data scientists, helping decision-makers accelerate innovation and reduce risk even when data is uncertain, sparse, or incomplete.

AI platform deploymentAI research and developmentmachine learninguncertainty quantification

Etegent is a defense technology company that delivers AI and software solutions for Intelligence, Surveillance, and Reconnaissance (ISR) operations. Founded in 1996 as Sheet Dynamics Ltd. and renamed Etegent Technologies in 2010, the company builds explainable AI, MLOps frameworks, and deployment-ready software for defense and intelligence missions, including missile defense, combat identification, and region monitoring.

AI model developmentEdge deploymentmachine learningMLOpsreal-time detection and trackingsignal and image processingsimulationsoftware developmentsoftware engineering

Fallen Angel Systems is an AI security research company founded in 2024 and an NVIDIA Inception Member. It builds AI products on an original IP architecture, with a lean team, and offers four products: Guardian, Judgement, Origin, and Origin Lens.

adversarial red teamingAI security researchconcept encodingprompt injection defense

INTRODUCING XENESE™“ We gather your data from every corner of your business. We make it real-time, visible, and actionable across your most critical systems. From edge nodes to enterprise cores, Xenese™ delivers the intelligence, trust, and automation to power what matters most.”Pascal Watty, CEO, First Genesis Inc.First Genesis You’ve invested in data. Now it’s time to turn it into outcomes you can prove.Xenese™ sits under your AI stack, making every data point, model, and decision fully traceable, tamper-proof, and ready to perform in real-time across edge, cloud, and hybrid environments. Get in touch Get in touch Intelligence Where the Action Is Unlike centralized platforms, Xenese enables decisions to happen at the edge on devices, assets, and systems without waiting on cloud latency or human intervention.Decisions You Can Defend Every outcome is explainable, traceable, and.

AI Engineeringdistributed systemsedge computingenterprise transformationentity-level machine learningreal-time AI infrastructureworkload orchestration

InnoTech Precision Medicine develops a minimally equipped medical diagnostics platform and a liquid biopsy assay that combines genetic profiling, phenotyping, and explainable AI to flag early-stage head-and-neck cancer in less than 30 minutes in a clinician's office. The company's mission is to make early cancer detection easy and accessible through a fast, painless test, and it is looking for strategic partners and collaborators.

genetic profilingliquid biopsymultimodal detectionphenotypingpoint-of-care diagnostics

JJT & Associates is an SBA-Certified Service-Disabled Veteran-Owned Small Business headquartered in Atlanta, Georgia, delivering secure cloud, AI/ML, DevSecOps, application development, collaboration and program management solutions for government agencies, public infrastructure, regulated organizations and enterprise teams. The company holds ISO 9001:2015 quality management certification and MBE/DBE credentials, and supports Team Black Fox as a subcontractor for NASA SEWP VI.

AI & machine learningapplication developmentcloud modernizationData StrategyDevSecOpsMLOpsprogram managementSecure dataSharePoint & collaboration

Komodo is a boutique data science consultancy for AI/ML, rapid prototyping, data engineering, and custom data-intensive R&D projects. For the last 9 years, they have helped organizations prepare their data, develop high-quality AI/ML models, and build real-time business intelligence systems. Their senior in-house team of data scientists, data engineers, and cloud architects overcomes data quality and integration challenges to create predictive modeling and analytical results.

AI/ML modelingalgorithm developmentbusiness intelligence dashboardscloud architecturecybersecurity-aware systemsData engineeringdata governancedata integrationdata quality assessmentdata warehouse designforecasting and simulationsIoTLLMsmodel training and validationpredictive modelingRAGrapid prototypingsignal processingsupervised learning