Lead Semantics : Transform Unstructured Data into Explainable Knowledge that De-Risks & Strengthens Enterprise AI
Prasad Yalamanchi
Founder
TextDistil ingests multimodal unstructured data (text, video, audio, images, network data and more) along with data from structured databases, and transforms it into a domain-aligned knowledge graph grounded in industry ontologies. The resulting graph besides serving AI workflows can be queried in natural language, explored through rich visualizations, and accessed via W3C-standard graph query languages and APIs.
The Journey behind TextDistil
Lead Semantics was founded on a simple but powerful belief which is AI becomes truly valuable only when it can compute with meaning. This philosophy first took shape in 2016 when the company introduced a semantic BI platform that quickly earned industry recognition. Drawing on deep expertise in computer science, computational linguistics, and knowledge representation, Lead Semantics steadily evolved its technology, integrating LLMs as they rose to prominence.
Yet, even as LLMs dazzled the world, their limitations hallucinations, weak explain ability, shallow reasoning, and poor domain grounding kept most enterprises stalled at the proof-of-concept stage. These gaps paved the way for a more dependable alternative which is neuro-symbolic AI, a hybrid approach that blends the power of neural models with the precision of symbolic reasoning.
Lead Semantics emerged as one of the earliest global adopters of this approach, and its flagship platform, TextDistil, reflects that pioneering vision. By combining modern LLMs with semantic graph technology and operating natively with domain ontologies, TextDistil dramatically reduces hallucinations, enhances reasoning depth, and ensures complete explain ability making it a timely and future-ready solution for enterprises.
Built on a tightly integrated neuro-symbolic architecture, TextDistil offers a comprehensive product suite tailored for real-world deployment. It enables the automatic generation of ontology-aligned knowledge graphs from diverse structured and unstructured sources, while also providing natural-language search and querying across vast volumes of multimodal data documents, videos, audio, images, and more as well as structured systems such as SAP, Odoo, Oracle, SQL Server, Postgres, and MySQL.
Together, these capabilities unlock deep, actionable insights for business users in simple, everyday English, transforming traditional BI into a new era of transparent, high-value knowledge analytics. “Ground AI in domain semantics, and you eliminate hallucinations while gaining full explain ability. That’s what TextDistil brings to the enterprise”, says Prasad Yalamanchi, Founder & CEO of Lead Semantics.
Approach to Tailoring Intelligence for Every Domain
At Lead Semantics, TextDistil deployments are guided by the core belief: AI is only as effective as its understanding of the domain. Whatever the domain, be it ESG, finance, insurance, healthcare, or media, etc. we capture semantics of the domain as ontologies, taxonomies, and controlled vocabularies, which form TextDistil’s configuration layer.
Once aligned to the domain, TextDistil ingests multimodal data including documents, images, video, and structured sources and transforms it into machine-actionable, ontology-grounded knowledge. By combining the language capabilities of large language models with the sophisticated reasoning and domain-specific guardrails of knowledge graphs, TextDistil delivers accurate, explainable, and context-aware intelligence.
Real-world deployments demonstrate its impact: sales teams at a global manufacturer can now search in English and obtain precise product answers without IT support; a national broadcaster enriched metadata to drive stronger content recommendations and a hospital network built personal health graphs to advance individualized care.
Common onboarding challenges, such as limited domain expertise, the rapid evolution of LLMs, and scarce semantic technology skills, are effectively addressed through expert collaboration, continuous R&D, and robust internal training.
“Our value is not just enabling successful GenAI projects by mitigating LLM weaknesses, but transforming unstructured and structured data of the enterprise into auditable and actionable knowledge”, says Prasad Yalamanchi.
Future Vision
With demand for semantically grounded AI rising, Lead Semantics is scaling TextDistil’s multimodal capabilities and accelerating its global reach. The roadmap focuses on deeper integration of video/image intelligence, ontology driven orchestration for robust agent workflows, streamlined ontology governance, and richer enterprise integrations.
Backed by a proven hybrid neuro-symbolic AI approach, industry recognition, and production deployments across sectors, it aims to establish TextDistil as the leading AI solution that turns unstructured enterprise data into governed, decision-ready knowledge - positioning semantic computing as the essential complement to generative AI in the enterprise.
At Lead Semantics, we see the future of enterprise AI in transforming every form of data into trustworthy, actionable knowledge - powering smarter, faster, and more transparent decisions
Together, these capabilities unlock deep, actionable insights for business users in simple, everyday English, transforming traditional BI into a new era of transparent, high-value knowledge analytics. “Ground AI in domain semantics, and you eliminate hallucinations while gaining full explain ability. That’s what TextDistil brings to the enterprise”, says Prasad Yalamanchi, Founder & CEO of Lead Semantics.
Approach to Tailoring Intelligence for Every Domain
At Lead Semantics, TextDistil deployments are guided by the core belief: AI is only as effective as its understanding of the domain. Whatever the domain, be it ESG, finance, insurance, healthcare, or media, etc. we capture semantics of the domain as ontologies, taxonomies, and controlled vocabularies, which form TextDistil’s configuration layer.
Once aligned to the domain, TextDistil ingests multimodal data including documents, images, video, and structured sources and transforms it into machine-actionable, ontology-grounded knowledge. By combining the language capabilities of large language models with the sophisticated reasoning and domain-specific guardrails of knowledge graphs, TextDistil delivers accurate, explainable, and context-aware intelligence.
Real-world deployments demonstrate its impact: sales teams at a global manufacturer can now search in English and obtain precise product answers without IT support; a national broadcaster enriched metadata to drive stronger content recommendations and a hospital network built personal health graphs to advance individualized care.
Common onboarding challenges, such as limited domain expertise, the rapid evolution of LLMs, and scarce semantic technology skills, are effectively addressed through expert collaboration, continuous R&D, and robust internal training.
“Our value is not just enabling successful GenAI projects by mitigating LLM weaknesses, but transforming unstructured and structured data of the enterprise into auditable and actionable knowledge”, says Prasad Yalamanchi.
Future Vision
With demand for semantically grounded AI rising, Lead Semantics is scaling TextDistil’s multimodal capabilities and accelerating its global reach. The roadmap focuses on deeper integration of video/image intelligence, ontology driven orchestration for robust agent workflows, streamlined ontology governance, and richer enterprise integrations.
Backed by a proven hybrid neuro-symbolic AI approach, industry recognition, and production deployments across sectors, it aims to establish TextDistil as the leading AI solution that turns unstructured enterprise data into governed, decision-ready knowledge - positioning semantic computing as the essential complement to generative AI in the enterprise.
