What is our primary use case?
We created a talent intelligence platform called MAIA. MAIA fuses four advanced AI technologies: Reactive AI, Generative AI, Reasoning AI, and Agentic AI to transform how organizations discover, assess, manage, develop, deploy, and hire talent. MAIA leverages AI, machine learning, and predictive analytics to create a Skillscape™ or talent landscape that supports decision-making by leaders. A key element is MAIA’s taxonomy and ontology.
MAIA’s foundational technology is a common language infrastructure that enables skills-based hiring and workforce mobility by providing a shared language for the workforce ecosystem. It decodes sector-specific jargon into universally understood competencies. MAIA unlocks hidden talent by revealing qualified candidates that traditional hiring processes overlook because their experience is described in unfamiliar terminology and is the key to faster, more successful career pivots across sectors. MAIA’s unified skills ontology is a comprehensive framework that understands the hierarchical relationships between skills, proficiency levels, and competency clusters and their relative importance, required proficiency levels, and contextual applications. It creates a universal skills currency that holistically demonstrates each person’s value.
MAIA is fast and proactive. Labor market conditions shift rapidly, and MAIA’s insights reveal talent attrition and other talent leaks impacting the organization. MAIA can shorten recruitment cycles to one hour. A continuous flow of people into the organization’s marketplace obliterates hiring cycle time and creates an on-demand talent flow. MAIA eliminates friction and frustration and replaces them with insight and revelation.
Key capabilities include intelligent document processing that extracts insights, skills, and other talent factors from any document type, including resumes, transcripts, certifications, coursework, forms, and military records. It also includes geolocation-based Skillscape™ or talent landscape that identifies skill concentrations and competitive landscapes, real-time candidate and employee assessments using MAIA’s taxonomy and ontology to measure skills, proficiency levels, competencies, and career paths against thousands of jobs, roles, work assignments, and correlated Knowledge, Skills, Abilities, and Tasks (KSATs). Additional capabilities include automated sourcing that continuously scans talent marketplaces for perfect-fit candidates and cross-sector analysis that recognizes transferable skills from any background. Built with federal-grade security (FedRAMP, DoD IL5), this platform delivers hypersonic efficiency in recruitment, hiring, and workforce deployment while maintaining full compliance and transparency.
Karini AI enabled our subject matter experts to quickly build knowledge graphs and develop multiple agents that are seamlessly integrated with our HR platform via API.
How has it helped my organization?
The Karini platform empowered our SMEs to move from idea to experimentation in hours and to production-grade agents in days, compared to months and years with our previous, traditional software development approach. We independently built and deployed over 50 agents within the platform and integrated them into our core platform via API, keeping development cycles cleanly separated.
What is most valuable?
Karini delivered no-code recipes for building knowledge bases, processing data, and creating agents. These recipes dramatically reduced the Agentic AI learning curve, allowing our SMEs to apply their domain expertise directly. The Karini architecture supported our FedRAMP/DoD IL5 authorizations, meeting compliance requirements for government customers. The Karini GenAI Foundation platform, spanning data integration, agent lifecycle management, and governance, was critical to scaling successfully in production. It is not just about building agents, but about scaling them for the enterprise.
What needs improvement?
The Karini team is responsive and continuously innovating. Scaling this responsiveness is critical to meet the rapid development of generative AI technologies. Karini’s Forward-Deployed Engineers provide instant feedback to Karini’s engineers, and the deployment of enhancements or novel developments continues to keep pace with the overall acceptance of our customers. I expect that demand will intensify quickly, and Karini’s capability to provide near-real-time enhancements is critical to our ability to meet that demand.
Which solution did I use previously and why did I switch?
We previously attempted to build our Agentic AI platform using an outsourced professional services partner. After two years, we could only deploy a single use case, resulting in heavy custom code that quickly became technical debt. As new models and techniques emerged, the custom solution immediately became obsolete.
How was the initial setup?
Karini’s pricing was attractive, with an all-in model that allowed us to deploy three environments aligned with our development instances. We subscribed to Karini’s Forward-Deployed Engineer program, which trained our business experts and provided advisory support as needed. The setup was straightforward, leveraging a Terraform module, and patching has been equally simple.
What's my experience with pricing, setup cost, and licensing?
Karini’s pricing was attractive, with an all-in model that allowed us to deploy three environments aligned with our development instances. We subscribed to Karini’s Forward-Deployed Engineer program, which trained our business experts and provided advisory support as needed. The setup was straightforward, leveraging a Terraform module, and patching has been equally simple.
Which other solutions did I evaluate?
We evaluated several open-source platforms.
What other advice do I have?
The Karini team understands how to operationalize sophisticated GenAI business solutions at enterprise scale. For organizations serious about adopting GenAI internally or in their product set, Karini’s platform allows for rapid experimentation that does not require staffing up with data scientists, machine learning specialists, or AI practitioners. Instead, using Karini’s Forward-Deployed Engineers paired with deep subject matter experts dramatically expedites experimentation to production deployments. The result is a powerful cycle of experimentation leading to rapid deployment and testing of prototype solutions with customers, and production deployment in days, not weeks, months, or years.
