Reasoning Engine

REASONER.DEV

An editorial forge for structured reasoning. Illuminate logic, anchor structure, and elevate every step of the thinking process.

Where logic meets craft

Logic Tree

Structured decomposition of complex problems into branching logical pathways. Each node represents a decision point in the reasoning chain.

reason.decompose(problem)

Identify premises and axioms
Map dependency relationships
Evaluate branching conditions
Prune contradictory paths

Reasoning Output

Synthesized conclusions drawn from validated logic chains. Each output carries provenance metadata linking back to its supporting evidence.

reason.synthesize(chains)

confidence 0.94

validity verified

depth 4 layers

branches 12 evaluated

Conclusion

Final validated reasoning products. Conclusions that have survived all logical scrutiny, complete with confidence metrics and supporting chain references.

reason.conclude(validated)

Reasoning Complete

The deductive chain holds across all 12 evaluated branches. No contradictions detected. The argument is formally valid with empirical support at confidence level 0.94.

Input Processing

Raw propositions and hypotheses enter the reasoning forge. Natural language statements are parsed into formal logical representations for systematic evaluation.

reason.parse(input, { formal: true })

Proposition "All valid arguments preserve truth"

Hypothesis "Deductive closure is computable"

Constraint "Consistency required across branches"

The Reasoning Pipeline

From raw input to validated conclusion, every step is illuminated.

Parse

Natural language input is tokenized and converted to formal logical notation. Ambiguities are flagged for resolution.

Decompose

Complex propositions are broken into atomic units. Dependencies between units are mapped as a directed acyclic graph.

Evaluate

Each logical branch is tested for validity. Contradictions are pruned. Consistent chains are preserved and scored.

Synthesize

Validated chains converge into final conclusions. Confidence metrics and provenance data are attached to each output.

Capabilities

Chain of Thought

Step-by-step reasoning traces that make the invisible visible. Every inference is logged and auditable.

Multi-Branch Analysis

Explore multiple reasoning paths simultaneously. Compare outcomes across branches to find optimal conclusions.

Contradiction Detection

Automatic identification of logical inconsistencies. Flagged contradictions prevent invalid conclusions from propagating.

Formal Verification

Machine-checked proofs for critical reasoning chains. Mathematical rigor applied to real-world arguments.

Reasoning API

Integrate structured reasoning into any application. RESTful endpoints for parse, decompose, evaluate, and synthesize.

Knowledge Graphs

Reasoning chains connected in rich semantic networks. Traverse relationships between concepts, evidence, and conclusions.

In Practice

example.reason

import { Reasoner } from 'reasoner.dev';

const engine = new Reasoner({
  mode: 'deductive',
  depth: 4,
  pruneContradictions: true
});

// Parse natural language into formal logic
const premises = engine.parse([
  "All developers value clear reasoning",
  "Clear reasoning requires structured tools",
  "reasoner.dev provides structured tools"
]);

// Build and evaluate the logic tree
const tree = engine.decompose(premises);
const result = engine.evaluate(tree);

// Synthesize conclusion
const conclusion = engine.synthesize(result);
// => { valid: true, confidence: 0.94 }