Blinkt AI®
Your LLM has general knowledge.
Blinkt gives it your mind.
Blinkt AI is the self-improving reasoning layer for agents.
Agents live in loops: observe → think → act. Blinkt powers this cycle by turning 10M-character contexts into an adaptive world model via a single WebSocket—building intelligence that gets smarter with every interaction.
Zero extra infrastructure.
One WebSocket. Twelve operations. Gets smarter on your data.
One persistent WebSocket gives you instant access to entity extraction, keyword analysis, causal reasoning, reranking, and knowledge graphs — all in the same conversation. Build smarter, faster agents with zero extra infrastructure.
Agents live in loops: observe → think → act → observe. Blinkt collapses the patchwork — chain any operation without reconnecting, auto-batch up to 10M-character contexts, and let the reranker improve automatically with every interaction. The more your pipelines run, the sharper their institutional memory and reasoning become.
One connection. Every NLP operation you need.
Most RAG and agentic pipelines stitch together separate services for chunking, embedding, reranking, entity extraction, and reasoning. Blinkt replaces that patchwork with a single WebSocket connection — twelve operations across three tiers, all returning structured JSON.
Start with segmentation. Add coreference resolution. Layer in reranking. Adopt causal analysis. Each operation is one more message on the same connection — no new integrations, no new vendors.
Foundational
Sentence segmentation
Entity & keyword extraction
Text normalization & cleaning
Text vectorization
Coreference resolution
Advanced
All Foundational features
Causal relationship extraction
Temporal sequencing
Topic modeling
Expert persona generation
Contextual reranking
Semantic chunking
Orchestration
All Advanced features
Knowledge graph construction
Multi-hop causal chaining
Multi-agent expert evaluation
Unified entity resolution
Cross-chunk synthesis
Probabilistic quality metrics
Model fine-tuning add-on
It gets smarter the more you use it.
Blinkt automatically fine-tunes your cross-encoder reranker based on usage, then pushes the versioned model to your Hugging Face repo. No training data to prepare. No pipeline to manage.
Every query-document interaction becomes a training signal. The more your application is used, the more precisely it retrieves. You own the model — it lives in your account, versioned and auditable.
This is the self-improving loop: Every time your users query the API, the reranker learns their domain, retrieval gets sharper, hallucinations drop — and they keep coming back for more.
Causal reasoning no other API offers.
Embedding search finds what's similar. Blinkt finds what caused what — and when.
The Insights tier implements Pearl’s Ladder of Causality: extracting cause-and-effect relationships, reconstructing temporal sequences from non-sequential narratives, and building traversable knowledge graphs with typed entities, causal edges, confidence scores, and counterfactual analysis.
No other NLP API exposes causal extraction and temporal reasoning as a real-time, managed orchestration. This lets your LLM answer “why did this happen?” and “what would have happened if…?” — not by guessing from embeddings, but by tracing structured evidence.
Developer friendly by design.
One persistent WebSocket. Send JSON. Get JSON back.
Pass us a single text object — up to 10 million characters — and we automatically handle chunking, batching, and parallel processing for you. No queues, no rate-limit juggling — just results.
