OrchestrAI
Route every query to the optimal reasoning approach. OrchestrAI analyzes incoming requests in real time and dispatches them to the best-fit model or reasoning engine — symbolic, case-based, neural, or hybrid — based on complexity, cost constraints, and latency requirements. Reduce API costs by up to 60% without sacrificing answer quality.
Key Features
Everything you need to integrate OrchestrAI into your production systems.
Intelligent Routing
Classify query complexity and automatically select the optimal reasoning engine. Simple factual lookups go to fast models; multi-step reasoning goes to deep thinkers.
Multi-Model Comparison
Run the same query across multiple models in parallel and return the highest-confidence answer. Built-in consensus scoring identifies when models agree and when they diverge.
Confidence Scoring
Every response includes a calibrated confidence score derived from model agreement, reasoning chain coherence, and historical accuracy on similar query types.
Fallback Chains
Define cascading fallback strategies. If the primary model times out or returns low confidence, OrchestrAI automatically escalates to the next model in the chain.
API Reference
Production-ready REST API. All requests require a valid API key via Authorization header.
/api/v1/orchestrai/routeRoute a query to the optimal model. Accepts a query string, optional constraints, and returns the routed response with metadata.
/api/v1/orchestrai/compareRun a query across multiple models simultaneously. Returns ranked responses with individual confidence scores and consensus analysis.
curl -X POST https://api.bolorintelligence.com/api/v1/orchestrai/route \
-H "Authorization: Bearer bolor_sk_..." \
-H "Content-Type: application/json" \
-d '{
"query": "Analyze Q4 revenue trends and predict Q1 outlook",
"context": {"department": "finance"},
"preferred_approach": "hybrid"
}'Use Cases
See how teams are using OrchestrAI in production today.
Complex Decision Support
Financial institutions use OrchestrAI to route risk assessment queries to symbolic reasoning for rule-based checks and neural models for pattern recognition, combining both for comprehensive analysis.
Research Analysis
Research teams route literature review queries to cost-effective models and reserve expensive deep-reasoning models for hypothesis evaluation, cutting costs while maintaining rigor.
Multi-Perspective Reasoning
Legal teams use the compare endpoint to get multiple model perspectives on contract clauses, identifying consensus interpretations and flagging areas where models disagree.
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Start Building with OrchestrAI
Get your API key and make your first call in under 5 minutes. Free tier includes 100 API calls per month.