Frost & Sullivan Names Seekr Global Company of the Year in AI Trust & Validation

Frost & Sullivan recognizes Seekr's integrated approach to explainability, defensibility, and sovereign AI deployment, helping enterprises and government agencies adopt AI and autonomous agents with greater confidence and control.

SAN ANTONIO, Nov. 4, 2026 /PRNewswire/ -- Frost & Sullivan today announced that it has named Seekr^® the 2026 Global Company of the Year in the AI Trust & Validation industry, recognizing the company's differentiated approach to AI accountability, explainability, model validation, and sovereignty. As organizations accelerate the adoption of artificial intelligence across enterprise and government operations, the need for reliable, explainable, and secure AI has become increasingly critical. Seekr's integrated platform helps organizations move beyond AI performance alone to establish greater transparency, maintain human oversight, and retain control over how AI systems operate and make decisions.

Company of the Year is Frost & Sullivan's top honor, recognizing the market participant that exemplifies visionary innovation, market-leading performance, and unmatched customer care. Frost & Sullivan recognized Seekr for embedding trust into the foundation of its AI architecture. Through an approach centered on observability, explainability, contestability, and sovereignty, the company addresses the challenges organizations face as AI systems move from experimentation into operational environments. Rather than simply monitoring system behavior, Seekr's technology helps organizations understand why AI systems reach particular conclusions, trace, and evaluate the reliability of those conclusions, and challenge or correct outcomes when necessary.

"As AI systems become more autonomous, establishing trust requires more than strong performance on static benchmarks. Models can behave differently in real-world environments, and when agents act on flawed observations, those errors can compound across successive reasoning and action cycles," said Karyn Price, Industry Director at Frost & Sullivan. "Seekr addresses this challenge through an architectural framework centered on observability, explainability, contestability, and sovereignty, translating these principles into practical capabilities for governing AI in operational environments."

Seekr's strategy focuses on helping organizations deploy AI across diverse infrastructure environments while maintaining consistent standards for accountability, security, and performance. Its SeekrFlow™ platform supports deployment in the cloud, on-premises, at the edge, and in fully air-gapped environments. This flexibility enables enterprises and government agencies to apply AI to sensitive information while retaining control over their data, infrastructure, and operational requirements.

Innovation remains central to Seekr's approach. Its portfolio includes SeekrGuard™, SeekrIntel™, and SeekrGeo™, built on SeekrFlow™ to support organizations across the AI lifecycle. By combining deployment flexibility with tools for validation and explainability, Seekr helps customers address the practical challenges of implementing AI in environments where accuracy, transparency, and accountability are essential.

Frost & Sullivan highlighted several capabilities that distinguish Seekr's approach to AI trust and validation:

• Evidence-based explainability: Seekr's attribution framework traces decisions to relevant training data, runtime context, model reasoning patterns, and agent behavior. Explanations are evaluated for faithfulness, sufficiency, plausibility, and consistency, helping organizations better understand the basis for AI-generated outcomes.
• Sovereign and model-agnostic deployment: SeekrFlow supports cloud, on-premises, edge, and air-gapped deployments, allowing organizations to select appropriate models and infrastructure while maintaining full ownership and control over sensitive data.
• Risk-aligned and right-sized model validation: SeekrGuard enables enterprise and government teams to evaluate models against their own risk factors and operational requirements. This supports informed model selection and the ability to choose the least resource-intensive model proven to meet their needs and continued evaluation after deployment.
• Measurable customer outcomes: In one reported deployment, accounting firm Stephano Slack reduced 401(k) auditing time by 90%. Another customer reported potential annual savings of $1.5 million to $2.5 million.

Seekr's focus on customer outcomes is complemented by its emphasis on security and operational control. Its SOC 2 Type II attestation and CMMC Level 2 certification support its work with organizations that require established security practices when deploying AI in sensitive and mission-critical environments. These capabilities position Seekr to address the needs of organizations seeking to scale AI adoption without compromising governance, data protection, or accountability.

"Enterprise and government customers alike are demanding more from AI than giving their valuable data away to train, wishfully hoping an agent doesn't go rogue, and then dealing with large closed-weight model bills at the end of the month," said Rob Clark, President of Seekr. "Our platform brings AI agents and models that are explainable and defensible from start to finish, optimized for size and higher performance, all running on the customer's terms in their environment. Frost & Sullivan's recognition validates the approach Seekr has taken, and shows why our customers get to production quicker with confidence." 

As organizations adopt a mix of proprietary, open-source, cloud-based, on-premises, and air-gapped AI models, the ability to apply consistent governance across different systems is becoming increasingly important. Seekr's integrated approach addresses this need by bringing explainability, defensibility, validation, and deployment flexibility together within a unified platform. Its focus on making AI decisions more transparent and contestable supports organizations as they work to establish appropriate oversight for increasingly autonomous systems.

Frost & Sullivan independently evaluated multiple nominees against two core dimensions: Visionary Innovation & Performance and Customer Impact. The assessment considered factors including the ability to address unmet needs, leadership focus, implementation of best practices, price/performance value, customer ownership experience, and brand equity. Seekr's recognition reflects its approach to translating AI trust principles into practical capabilities designed to meet evolving enterprise and government requirements.

Frost & Sullivan's Best Practices Recognition program identifies companies demonstrating outstanding achievements in leadership, technological innovation, customer service, and strategic product development. Through in-depth interviews, market analysis, and secondary research, industry analysts evaluate market participants to identify organizations establishing best practices and delivering differentiated value in their respective industries.

To read the full Frost & Sullivan report, visit https://www.frost.com/wp-content/uploads/2026/10/Seekr-Final-Write-up.pdf. To learn more about Seekr, visit seekr.com.

Frost & Sullivan Best Practices Recognition

Frost & Sullivan's Best Practices Recognitions honor companies across regional and global markets that exhibit exceptional achievement and consistent excellence in areas such as leadership, technological innovation, customer experience, and strategic product development. Each recognition is the result of a rigorous analytical process in which Frost & Sullivan industry experts benchmark performance through comprehensive interviews, deep-dive analysis, and extensive secondary research. The goal is to identify true best-in-class organizations that are driving transformative growth and setting new industry standards.

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About Seekr

Seekr is the leader in explainable, defensible AI built for critical decisions in environments that demand accuracy and accountability. Seekr's technology and products help enterprises and government agencies develop and deploy domain-specific large language models (LLMs), vision language models (VLMs) that understand the physical world, edge-based systems, and AI agents across a range of infrastructure environments, including sovereign deployments. Backed by robust verification and validation tools that surface the provenance, lineage, and intent behind every model decision, Seekr delivers AI that organizations can audit and trust across all modalities. Learn more at seekr.com.

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