Interview with Ravi Bommakanti, Chief Technology Officer at App Orchid
App Orchid Leads Enterprise AI Adoption with Agentic AI Platform
GSpeech's Chief Technology Officer, Ravi Bommakanti, heads App Orchid, a company dedicated to enabling enterprises to operationalize AI across their applications and decision-making processes. Their flagship product, Easy AnswersTM, allows users to interact with data using natural language to generate AI-powered dashboards, insights, and recommended actions.
The platform synthesizes structured and unstructured data, including real-time inputs and employee knowledge, into a predictive data fabric that supports strategic and operational decisions. With in-memory Big Data technology and a user-friendly interface, App Orchid streamlines AI adoption through rapid deployment, low-cost implementation, and minimal disruption to existing systems.
B汇动AI, in contrast to traditional AI systems, represents a shift from static execution to dynamic orchestration. According to Bommakanti, it signifies the movement from rigid, pre-programmed systems to autonomous, adaptable problem-solvers capable of reasoning, planning, and collaboration. what uniquely sets Agentic AI apart is its ability to leverage the distributed nature of knowledge and expertise. Traditional AI often operates within limited boundaries, strictly following predetermined paths. Agentic systems, on the other hand, can decompose complex tasks, identify the right specialized agents for sub-tasks, potentially discovering and leveraging them through agent registries, and orchestrate their interaction to synthesize a solution. Agents registries enable organizations to effectively 'rent' specialized capabilities as needed, similar to how human expert teams are assembled.
Google Agentspace is accelerating the adoption of agentic AI across enterprises by offering a unified foundation for deploying and managing intelligent agents connected to various work applications. By transforming siloed information into actionable intelligence via a common interface, Agentspace allows companies to leverage Google's powerful search and models like Gemini. App Orchid's role in this ecosystem is to function as a vital semantic enablement layer within the Agentspace environment. App Orchid uses an ontology-driven approach to build rich knowledge graphs from enterprise data, incorporating business context and relationships, which is crucial for agents to effectively interact and deliver meaningful business insights.
The primary obstacles faced by companies adopting agentic AI revolve around data quality, evolving security standards, and managing the distributed nature of enterprise knowledge and agent capabilities. App Orchid tackles these challenges by addressing the foundation through creating a semantic layer that provides context to disparate data sources. It also utilizes unique crowdsourcing features within Easy Answers to engage business users organization-wide to collaboratively identify and address data gaps and inconsistencies, significantly improving data reliability. Security is another critical issue, especially as agent-to-agent communication becomes more common. App Orchid implements security measures designed for these dynamic interactions to build robust agent-to-agent trust while maintaining governance without hindering necessary collaboration. Finally, harnessing distributed knowledge and capabilities effectively necessitates advanced orchestration, which App Orchid achieves through concepts like the Model Context Protocol (MCP).
Easy Answers facilitates natural language querying by connecting to various enterprise data sources, rapidly building a comprehensive knowledge graph, structuring data into business-centric entities called Managed Semantic Objects (MSOs), enriching them with metadata, and translating user queries into precise data queries. This democratizes data access and analysis, turning complex data exploration into a simple conversation. Easy Answers bridges siloed data by creating a unified semantic view and fosters trust through clear traceability and explainability. This combination effectively bridges technical data structures with business meaning, regardless of where the data physically resides.
App Orchid ensures transparency in insights, especially in regulated industries where data lineage is critical, by providing end-to-end data lineage tracking, methodology visibility, and natural language explanations. By incorporating role-based access controls, approval workflows for certain actions or reports, and comprehensive audit logs tracking user activity and system operations, it maintains insights as accurate, trustworthy, explainable, and defensible.
App Orchid empowers AI-generated insights to drive business outcomes by proposing concrete, contextually relevant recommendations for actions in response to identified patterns, trends, anomalies, or opportunities through its Generative Actions feature. These recommendations maintain human oversight by presenting them to the suitable users for review, modification, approval, or rejection. Once an action is approved, App Orchid seamlessly executes the workflow through integrations with operational systems.
The success of the Easy Answers platform hinges on its knowledge graphs and semantic data models, which elevate it beyond traditional Business Intelligence (BI) tools that often treat data as disconnected tables and columns devoid of real-world business context. The knowledge graph enables true natural language interaction, preserves critical business context, and provides adaptability and scalability—enabling the platform to evolve with the business as needs change.
App Orchid supports leading foundational models from multiple providers and facilitates the integration of custom AI/ML models into the Easy Answers workflow. This ensures the platform remains open and flexible, catering to the speed of AI evolution and respecting organizations' existing investments.
Looking ahead, App Orchid envisions a future where agentic AI adoption is driven by trends such as dynamic, composable, and collaborative ecosystems. This shift is being propelled by agent marketplaces, standardized agent-to-agent communication protocols, dynamic orchestration, and no-code/low-code agent design. App Orchid's role is to provide the crucial data understanding and accessibility that enables agentic AI to operate effectively and deliver valuable insights within the enterprise environment.
The democratization of decision intelligence through agentic AI elevates the role of the CTO. As data becomes more central to business strategy, CTOs are challenged to build data strategies that ensure data is not just available but also rich, reliable, accessible, and understandable. Their role evolves from managing IT infrastructure to becoming strategic organizers of organizational intelligence, championing adaptability, and fostering human-AI collaboration.
The platform developed by App Orchid, Easy Answers, not only focuses on data and cloud computing, but also integrates cybersecurity measures to ensure secure communication between agents in the AI ecosystem. In the future, as agentic AI becomes more prevalent, data-and-cloud-computing, technology, and artificial-intelligence will be indispensable in creating dynamic, composable, and collaborative ecosystems, where CTOs will play a significant role in leveraging these technologies to democratize decision-making processes and enable human-AI collaboration.
