All work

TitoTruth

Knowledge & Document Software · Claim Verification / NLP Platform

Turning free-form claims into structured semantic units for verification

TitoTruth uses a controlled semantic representation underneath AI reasoning. Free-form factual claims are decomposed and classified through a structured ontology, then evaluated using a combination of rules, embeddings, vector retrieval and LLM reasoning.

NLPVerificationVector searchAI product

The starting point

Unconstrained model reasoning is difficult to classify or evaluate consistently.

What had to change

The product needed a repeatable, structured representation of a claim.

What couldn't break

The ontology had to stay stable while the hybrid AI and retrieval stack around it evolved.

Why this was hard

The system has to bridge ambiguous natural language and deterministic structure.

What Datics changed

Datics built claim decomposition over a 114-token ontology, evaluated through semantic embeddings, vector retrieval, rules and LLM reasoning.

Claim decomposition

Free-form claims broken into semantic units.

114-token ontology

A controlled vocabulary underneath the reasoning.

Hybrid classification

Rules, embeddings and LLM reasoning combined for classification.

Vector-backed verification

Retrieval supports evidence for each unit.

Platform in action

Claim Intake

Where a free-form claim enters the system.

Semantic Decomposition

Where the claim becomes structured units.

Verification Workflow

Where units are classified and checked.

Engagement at a glance

Free-form factual claims can be decomposed into structured semantic units for more repeatable downstream classification and verification.

Semantic model
114-token ontology
Reasoning stack
Rules, embeddings, retrieval and LLMs
Status
Ongoing AI product

Under the hood

Datics role
AI product engineering across NLP classification, retrieval and decomposition.
Integrations
Qdrant vector search plus Anthropic and OpenAI model services.
Deployment
Dockerized application with asynchronous background processing.
Production boundary
AI verification and classification product.

Technology

FastAPIPythonPostgreSQLRedisCeleryQdrantSBERTAnthropic/OpenAIRegexDocker

What this unlocked

A structured semantic layer gives downstream verification and evidence workflows a repeatable representation to reason over rather than relying solely on opaque model interpretation.

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