AI Agents

Put the power of AI to work

BKOAI’s Multi-Modal Agents orchestrate LLM / VLM-powered multi-agent systems to automate complex tasks, enabling intelligent coordination, adaptive behavior, and seamless enterprise integration.

At BKOAI, we engineer multi-agent systems that transform static engineering data and operational silos into dynamic, actionable intelligence.
By combining NLP, retrieval-augmented generation (RAG), and symbolic reasoning under a collaborative agentic framework,
we help organizations accelerate compliance, capture critical expertise, and drive smarter, data-informed decisions.
Our solution encompasses four key domains:

Engineering Standards Intelligence

We convert complex engineering standards—often buried in thousands of static PDF pages—into structured, searchable knowledge assets. This enables teams to interact with regulatory and design information in a dynamic, intent-aware environment.

Parse engineering PDFs to extract hierarchies, parameters, and semantic relationships.

Build ontologies and graph databases capturing domain-specific logic.

Provide knowledge-augmented search that understands synonyms, design contexts, and regulatory nuances.

Accelerate compliance checks and enable consistent reuse of engineering standards.

Deep Research & Lessons Learned

We institutionalize hard-won operational knowledge by deploying deep-research agents that mine internal archives and generate context-aware insights. This reduces repetitive mistakes and preserves critical institutional memory..

Autonomously scan internal repositories, case studies, and post-mortem reports.

Synthesize lessons learned into tailored, actionable summaries for engineers and decision-makers.

Highlight historical root causes, design alternatives, and mitigation strategies.

Embed these insights directly into engineering workflows.

PI-to-Equipment Semantic Mapping

We create living knowledge graphs of operational environments by semantically linking raw PI data streams to physical assets and functional hierarchies, dramatically enhancing situational awareness.

Use NLP and symbolic reasoning to map PI tags to equipment entities.

Continuously refine mappings based on new operational inputs and feedback.

Build dynamic asset models that reveal interdependencies and functional contexts.

Improve monitoring, diagnostics, and predictive analytics.

Smart Field Engineering Assistant

We equip field teams with intelligent agentic assistants that understand nuanced technical queries and adapt to evolving knowledge—going far beyond static chatbots.

Task-routing agents classify user queries and delegate to specialized sub-agents.

Domain expert agents retrieve and synthesize precise technical answers.

Interactive reasoning agents ask clarifying questions, guide step-by-step troubleshooting, and recommend preventive actions.

Why AI Agents and
Foundation Models

Put the power of AI to work

Engineering Standards Intelligence

Deep Research & Lessons Learned

PI-to-Equipment Semantic Mapping

Smart Field Engineering Assistant

Our AI Agent Case Study

Get in touch

Why AI Agents andFoundation Models

Put the power of AI to work

Engineering Standards Intelligence

Deep Research & Lessons Learned

PI-to-Equipment Semantic Mapping

Smart Field Engineering Assistant

Our AI Agent Case Study

Why AI Agents and
Foundation Models