Senior Product Manager

Seekr achieves CMMC Level 2 certification for trusted AI deployment, setting the standard for operational AI in government. PR Newswire Certification Authorizes Seekr to Handle Controlled Unclassified Information for the Department of War, Validating Its Explainable AI Platform for Mission-Critical Environments RESTON, Va., July 7, 2026 /PRNewswire/ - As national security agencies accelerate the deployment of operational AI, Seekr today announced it has achieved Cybersecurity Maturity Model Certification (CMMC) Level 2 with a perfect score, validated by an independent Third-Party Assessment Organization (C3PAO) across all 110 NIST SP 800-171 controls and 320 assessment objectives. CMMC Level 2 is the Department of War's standard for any contractor that handles Controlled Unclassified Information - the sensitive, unclassified data that runs through most defense work, from technical specifications and contract details to personnel and program records. Starting November 10, 2026, third-party certification by a C3PAO becomes the default requirement for new contracts involving CUI, replacing the self-assessments previously accepted. According to the May 2026 Cyber AB Town Hall, only 1,391 organizations have achieved Final Level 2 certification through an independent C3PAO assessment - which represents fewer than 2% of the approximately 80,000 defense contractors the Department of War estimates will need it. Seekr is among that small group, and one of the few explainable, auditable AI companies in it, certified six months ahead of the November 10, 2026 mandate. The certification arrives at an inflection point. As federal agencies move AI from pilot to production across defense and intelligence missions, the question is no longer which models are most capable - it's which AI companies can be trusted to operate inside the contracts, classifications, and consequences those missions carry. Trustworthiness in operational AI is increasingly measured the same way the government measures it everywhere else: through independent audit. "In defense and intelligence, the question isn't whether the AI is powerful - it's whether the model, agents, and company behind it is accountable and transparent," said Seekr President, Rob Clark. "CMMC Level 2 certification, with a perfect score, is independent confirmation that Seekr meets the standard the mission requires. We hold our technology to that same standard: explainable AI that lets the operators and analysts making consequential decisions verify the answer, not just hope it's right" Speed without accountability isn't mission readiness. Seekr delivers both on one platform - built on customer data, fully owned and fully controlled, with the governance and explainability operational AI in national security requires. Seekr was built to help highly regulated industries trace every decision from data to outcome, across cloud, on-premise, air-gapped, or tactical edge environments. With SeekrFlow every outcome is explainable, and customers move from concept to prototype in days, and from prototype to production in weeks. The work ahead is bigger than any single certification. As defense and intelligence agencies move from AI experimentation to operational deployment, the platforms that earn a place in the mission will be the ones built to be questioned, audited, and held accountable. Seekr is built for that standard - and now certified to it.

Seekr, a leader in explainable AI, has partnered with Enabled Intelligence, a specialist in high-precision data labeling, to deliver trusted AI tools for enterprise customers. The partnership combines Seekr's SeekrFlow platform with Enabled Intelligence's expert-driven data annotation services. Enabled Intelligence employs US-based specialists, including geospatial analysts and former military personnel, to annotate complex data across multiple formats. This expert-led approach delivers greater precision than crowdsourced alternatives, reducing errors that cause model hallucinations. The combined offering includes enterprise-tailored language-vision models and pre-built AI agents for specialised use cases, including the SeekrGeo platform for geospatial reasoning. The partnership targets high-stakes industries including financial services, supply chain, and critical infrastructure, where accuracy and explainability are paramount.

Seekr's explainability-first approach earns Notable Challenger status from GAI Insights. June 30, 2026 Enterprise and federal AI buyers are looking past model capability alone to the infrastructure required to explain, audit, and control agents in production. GAI Insights named Seekr a Notable Challenger in its 2026 Corporate Buyers' Guide, highlighting its year-over-year momentum across both strategic value and market readiness, as well as its explainability-first approach to AI. This validates one of its core product beliefs: explainability belongs in the infrastructure layer. With agent adoption already underway, what remains unresolved is whether organizations can deploy agents in production with the control, evidence, and auditability their workflows require. Agents retrieve information, call tools, follow instructions, and produce outputs that can influence real decisions. With each step, the risk of error compounds, and so does the need for explainability. Organizations need to know what shaped the result, where it can be trusted, and where it needs to be challenged. A model that performs well in a demo is not the same as an AI system that can be governed in production. Enterprise teams need to trace outputs back to the context, data, tools, and model behavior that influenced them. They need evidence they can inspect, challenge, and use to improve the system over time. That is the foundation of SeekrFlow(TM). SeekrFlow gives organizations a complete, secure operating system for training, validating, deploying, and scaling trusted generative AI agents and applications. Explainability is built into how teams operate the system, adding trust and transparency from development to deployment and beyond. This matters because agentic AI does not fail in abstract ways. It fails inside retrieval, policy, tool use, data pipelines, and operating environments. Without visibility into those layers, teams are left guessing where the failure happened and how to fix it. SeekrGuard extends that foundation into model and agent evaluation. Instead of relying only on generic benchmarks, organizations can evaluate AI systems against their own business-specific and mission-specific criteria before deployment. This is especially important in enterprise, government, defense, and regulated environments where auditability is part of the deployment requirement. Teams need AI they can explain to technical reviewers, business owners, procurement teams, regulators, and mission stakeholders. Deployment control is part of that equation, too. Seekr supports SaaS, private cloud, on-premises, edge, and air-gapped environments so organizations can deploy trusted AI where their data, security, and operational requirements demand it. GAI Insights' recognition of Seekr reinforces what many AI buyers are already making clear: agent infrastructure has to be explainable, auditable, and defensible from the start. Seekr Technologies, Inc. is proud to continue building AI infrastructure organizations can explain and defend in real-world deployments. Agents are here. Trust is the next test. Explainability belongs in the infrastructure layer. AI evaluation has to match the environment. Trusted AI means deployment control. The new standard for enterprise AI.