T2K Text2Knowledge

A new layer for understanding

Beyond text.
Toward understanding.

Text2Knowledge is an AI ontology studio that turns language into living ontologies: structured maps of meaning, relationship, provenance, and impact. It helps teams convert clinical notes, research documents, policies, and conversations into knowledge they can inspect and query.

Explore Ontology Studio Read the Vision

Now building Ontology Studio. Seeking design partners in healthcare, research, and enterprise knowledge work.

Vision

Text is the visible trace. Knowledge is the structure beneath it.

Most software stops at search, summaries, or generated answers. Text2Knowledge is building a system that turns language into navigable structure so people can reason about what is connected, what is changing, and what matters.

Framework

From signal to meaning.

01

Text

Documents, conversations, notes, records, prompts, and stories. The visible signal.

02

Meaning

Entities, claims, emotions, symbols, intent, and interpretation.

03

Knowledge

Relationships, ontologies, causality, constraints, and context.

04

Impact

The consequences of meaning across people, systems, and decisions.

Standard AI Summary

"Patient is a 72-year-old male with CHF and COPD experiencing dyspnea and edema. He takes furosemide and metoprolol but has difficulty following his fluid restrictions."

Readable, but flat. Relationships between symptoms, diagnoses, and medications are implicit. No structured links to query or audit.

T2K Ontology

Patient(72M) + Diagnosis(CHF, COPD) + Symptom(Dyspnea, Edema bilateral LE) + Medication(Furosemide 40mg daily, Metoprolol 50mg BID) + Claim(inconsistent fluid restriction adherence, patient-reported) + Gap(no documented follow-up plan).

Facts are captured as typed, linked entities. Relationships, provenance, and gaps stay explicit and queryable.

Ontology Studio

An editable world model built from language.

Ontology Studio is an LLM-native workspace for converting unstructured language into knowledge maps that can be inspected, challenged, and extended.

  • Extract entities, concepts, claims, and value signals
  • Model relationships, hierarchies, and causal chains
  • Separate fact, interpretation, belief, and implication
  • Reveal contradictions, gaps, and downstream impact
  • Build shared understanding instead of isolated summaries
Source Clinical note

Patient is a 72-year-old male presenting with worsening dyspnea and bilateral lower extremity edema. History of CHF and COPD. Current medications include furosemide 40mg daily and metoprolol 50mg BID. Patient reports inconsistent adherence to fluid restriction.

derived from note
Extracted Ontology 7 entities
  • Confidence: 99%
    Rule: Person Entity Link
    Patient 72M
  • Confidence: 98%
    Rule: Clinical Diagnosis Match
    Diagnosis CHF
  • Confidence: 98%
    Rule: Clinical Diagnosis Match
    Diagnosis COPD
  • Confidence: 96%
    Rule: Symptom Classification
    Symptom Dyspnea
  • Confidence: 94%
    Rule: Symptom Classification
    Symptom Edema, bilateral LE
  • Confidence: 98%
    Rule: Med-Extract-V2
    Medication Furosemide 40mg daily
  • Confidence: 98%
    Rule: Med-Extract-V2
    Medication Metoprolol 50mg BID
Relationships
  • Dyspnea symptom of CHF
  • Edema symptom of CHF
  • CHF comorbid with COPD
  • Furosemide prescribed for CHF
Claim patient-reported

Inconsistent adherence to fluid restriction

Flagged: gap moderate confidence

Patient reports inconsistent fluid restriction adherence — no documented follow-up plan or monitoring note.

Background

Text2Knowledge is built on 25 years of work in NLP, machine learning, and applied data. Our expertise spans high-consequence domains: from healthcare and clinical knowledge systems to bioinformatics and complex social data. We specialize in turning unstructured language into structured understanding that drives reliable decisions.

The T2K Difference

Beyond Probabilistic Language: While LLMs generate fluid text, Text2Knowledge transforms those signals into interpretable structure. We bridge the gap between AI-generated language and structured, auditable outputs that clinicians, researchers, and strategists can inspect, challenge, and build on.

Use Cases

Start where text carries consequence.

A

Healthcare

Transform dense clinical language into structured context for safer reasoning, coordination, and decision support. Ontology Studio surfaces conflicts, missing context, and downstream implications that narrative text obscures. Compatible with clinical knowledge standards including FHIR and SNOMED-CT structures.

B

Research and Strategy

Turn fragmented sources into knowledge maps that expose hidden assumptions and causal leverage. Map literature, data, and expert claims into a shared ontology that teams can query, challenge, and extend.

C

Enterprise Knowledge

Connect internal documents, policies, conversations, and workflows into a queryable operational ontology. Surface conflicts across teams, track how institutional knowledge evolves, and close gaps before they cause failures.

About

What we're building.

Text2Knowledge is building infrastructure for structured understanding — starting where language is densest and the stakes are highest. Our platform is designed for realities that cross digital, physical, human, symbolic, and belief-shaped domains.

FAQ

Common questions about Text2Knowledge.

Text2Knowledge turns complex language into structured, auditable knowledge for teams working in high-stakes domains.

What is Text2Knowledge?

Text2Knowledge is an AI ontology studio and knowledge extraction platform. It converts unstructured text into typed entities, relationships, claims, provenance, and gaps that teams can inspect and query.

How is it different from an AI summary?

AI summaries compress a document into prose. Text2Knowledge preserves structure, so diagnoses, symptoms, medications, evidence, and uncertainty remain explicit instead of being flattened into one paragraph.

Who is Ontology Studio for?

Ontology Studio is for healthcare, research, and enterprise knowledge teams working with dense, high-stakes documents that need auditable outputs and shared context.

What text can Text2Knowledge structure?

It is designed for clinical notes, research papers, policies, reports, transcripts, and other complex documents where relationships, provenance, and downstream impact matter.

Is Ontology Studio available now?

Ontology Studio is in active development. We are onboarding design partners who want to shape the product before general availability. Reach out to join the early access program.

How does Text2Knowledge handle sensitive data?

Data security and compliance are foundational to our architecture. We are building toward HIPAA-readiness and will support on-premise deployment for teams with strict data residency requirements.

Get started

Become a design partner

We're looking for researchers, clinicians, and knowledge teams to shape Ontology Studio from the ground up.

  • Teams working with complex, high-stakes documents
  • Clinicians focused on care coordination
  • Researchers mapping causal links and evidence
  • Knowledge teams building structured workflows

Design partners get early access, direct input on the product roadmap, and priority onboarding at launch.

Get involved

Or email partners@text2knowledge.com

Get in touch

Text2Knowledge is pre-seed and actively seeking advisors with healthcare AI or clinical informatics networks, and early-stage capital to accelerate development.

Start a conversation

Or email hello@text2knowledge.com