Deterministic AI for
Human Friction. Delivered.

POST /v1/graph/query
{
  "query": "MATCH (a:Actor)-[r:ASSERTS]->(c:Claim) WHERE c.type = 'RedLine' RETURN a, r, c",
  "graph_id": "case_2025_001",
  "include_provenance": true
}

{
  "actors": [
    {
      "id": "a1",
      "label": "CEO Smith",
      "role": "principal",
      "confidence": 0.98
    }
  ],
  "claims": [
    {
      "id": "c1",
      "type": "RedLine",
      "text": "Minimum price $2.5B",
      "provenance": {
        "source": "LOI_v1.2",
        "timestamp": "2025-02-25"
      }
    }
  ],
  "edges": [
    {
      "from": "a1",
      "to": "c1",
      "type": "ASSERTS",
      "confidence": 0.95
    }
  ]
}

pip install tacitus-sdk

from tacitus import TacitusClient

client = TacitusClient(api_key="YOUR_KEY")

# Ingest a document
graph = client.ingest(
    source="contract_dispute_2025.pdf",
    graph_id="case_001"
)

# Query the graph
results = client.query(
    graph_id="case_001",
    match="(a:Actor)-[:ASSERTS]->(c:Claim)",
    where="c.type = 'RedLine'",
    include_provenance=True
)

npm install @tacitus/sdk

import { TacitusClient } from '@tacitus/sdk';

const client = new TacitusClient({ apiKey: process.env.TACITUS_KEY });

// Ingest a source
const graph = await client.ingest({
  source: 'contract_dispute_2025.pdf',
  graphId: 'case_001',
});

// Query actors and claims
const results = await client.query({
  graphId: 'case_001',
  match: '(a:Actor)-[:ASSERTS]->(c:Claim)',
  where: "c.type = 'RedLine'",
  includeProvenance: true,
});