Tacnode powers agentic AI, RAG applications and vector search from one system, providing subsecond context when it's needed most.
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AI/ML teams waste time managing stale feature stores, syncing model outputs, and hacking together retrieval. Smarter models and agents need instant access to fresh, contextual data.
Point-in-time feature generation often relies on daily batch updates — starving your models of real-world signals they need right now.
Retrieving inference-time context often requires stitching together APIs, caches, and databases — making real-time intelligence brittle and slow.
Training and evaluation data lags behind real-world conditions, degrading model relevance and leaving agents unable to adapt midstream.
From data ingestion to inference to retraining, Tacnode gives machine learning teams instant access to the freshest signals and the flexibility to adapt continuously. No more batch delays, brittle pipelines, or context gaps.
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Generate features from streaming signals as they happen — not hours or days later. Tacnode lets you compute on fresh, cross-system context in real time, with no ETL gymnastics. That means faster iteration, better model inputs, and fewer surprises in production.
Models and agents only perform as well as the context they see. Tacnode retrieves enriched inference-time data from live sources in milliseconds — so you can serve smarter responses, personalize accurately, and act without stale-state risk.
Capture outcomes and behavior as they unfold. Tacnode streams telemetry, decisions, and downstream results back into your system instantly — enabling faster retraining, fine-tuning, and reinforcement learning cycles.
Stay current without reengineering your pipeline. Tacnode continuously feeds versioned, up-to-date data into your training workflows, preserving schema integrity and history while eliminating snapshot lag. Train like it's production — because it is.
Tacnode gives your AI systems instant access to live, contextual data — so they can decide, adapt, and improve without delay.
