Resources

Resources for AI automation, integration, and smarter operations

From our blog

Articles & insights

Еxploring the intersection of artificial intelligence, industrial automation, and the future of professional workflows.
A clear decision framework for when a micro-tool is enough—and when reliable automation needs custom integration.
What to verify before connecting tools—access scopes, secrets, logging, retention, and where sensitive data is allowed to flow.
How to track automation impact using cycle time, quality, and error-rate signals instead of vanity metrics.

guides

Practical Guides

Step-by-step resources to help you evaluate use cases, plan implementation, and roll out automation with confidence.

FAQ

Common questions

Everything you need to know about our products, frameworks, and enterprise AI approach.
CORTEXA Enterprise™ is TekFrameworks’ Distributed Cognitive Fabric that connects systems, models, agents, workflows, memory, governance, and telemetry into one accountable intelligence layer.
Yes. CORTEXA can connect with ERP, CRM, HRIS, ITSM, Finance systems, RAG pipelines, agent frameworks, MCP tools, and internal applications through its enterprise integration layer.
Yes. Governance is built into the architecture through policy controls, redaction, audit logs, decision traceability, memory controls, permissions, and bounded AI behavior.
CORTEXA DomainLM™ helps enterprises build domain-adaptive AI models using their own enterprise data, knowledge, workflows, and business context.
Yes. CORTEXA DomainLM™ is designed to adapt across domains including finance, healthcare, legal, manufacturing, and life sciences
Yes. CORTEXA DomainLM™ is designed to adapt across domains including finance, healthcare, legal, manufacturing, and life sciences.
Outputs are evaluated through structured benchmarks, validation checks, explainability, and traceability before deployment into enterprise workflows.
Yes. TekFrameworks provides advisory around AI strategy, decision frameworks, governance, roadmap development, prioritisation, and enterprise AI adoption.