# Tacnode — Shared Context for Automated Decisions > Markdown mirror of DialtoneApp's public top-site detail page for `tacnode.io`. URL: https://dialtoneapp.com/top-sites/tacnode.io/index.md Canonical HTML: https://dialtoneapp.com/top-sites/tacnode.io ## Summary - Domain: `tacnode.io` - Website: https://tacnode.io - Description: ai readable | score 16 | purchase read only - Label: ai_readable - Payment surface: Not available - Purchase boundary: read_only - Control boundary: unknown - Rank: 63232 ## robots ~~~text User-agent: * Allow: / Host: https://tacnode.io Sitemap: https://tacnode.io/sitemap-index.xml ~~~ ## llms ~~~text # Tacnode > Tacnode Context Lake™ is a shared, live, semantic context layer for AI systems and real-time decision-making. It keeps services, models, and agents operating on the same current context — preventing stale data, context silos, and conflicting decisions. PostgreSQL-compatible. Tacnode solves the core infrastructure problem of real-time AI: when multiple systems (fraud detection, personalization, AI agents, eligibility checks) evaluate the same situation using different, stale, or inconsistent data, they produce conflicting decisions. Tacnode Context Lake provides a single shared layer where every system reads the same live context. ## Product - [What Is a Context Lake?](https://tacnode.io/context-lake): The infrastructure imperative for real-time AI — why stale data causes AI failures and how Context Lake solves it. - [Product Overview](https://tacnode.io/product): Architecture, system design principles, and platform guarantees for Tacnode Context Lake. - [Context Gap](https://tacnode.io/context-gap): What a context gap is, why it happens when decision systems can't access complete, consistent, and current context, and how to close it. - [Pricing](https://tacnode.io/pricing): Start free on AWS Marketplace. Simple compute + storage pricing with no hidden fees. - [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-ofzyfzpx52yni): Try Tacnode free via AWS Marketplace. - [Forrester Report](https://tacnode.io/resources/forrester-context-lake-report): Forrester Consulting commissioned study on why current data architectures are failing AI initiatives and how context lakes enable AI-ready foundations. - [Compare](https://tacnode.io/compare): Compare Tacnode Context Lake to Snowflake, Databricks, Pinecone, and traditional databases. ## Platform Capabilities - [Decision Coherence](https://tacnode.io/decision-coherence): How Tacnode's three-pillar architecture — shared, live, and semantic context — eliminates incoherence at the infrastructure level. - [Horizontal Scalability](https://tacnode.io/horizontal-scalability): Horizontal scaling without limits — expanding and shrinking in seconds while fully online. - [Workload Isolation](https://tacnode.io/workload-isolation): Multi-tenant workloads run concurrently — batch ingestion won't slow real-time decisions. - [High Availability](https://tacnode.io/high-availability): Automated failover, zero-downtime upgrades, and no maintenance windows. ## Solutions - [Fraud Detection](https://tacnode.io/solutions/fraud-detection): Evaluate every transaction against customer history and network patterns within 50ms authorization windows. - [Personalization](https://tacnode.io/solutions/personalization): Real-time recommendations based on live session behavior, inventory availability, and customer history. - [Credit & Underwriting](https://tacnode.io/solutions/credit-underwriting): Dynamic risk scoring against live context — decisions that reflect reality, not yesterday's snapshot. - [Identity & Policy Enforcement](https://tacnode.io/solutions/security): Atomic access control, rate limiting, and policy enforcement. ## Documentation - [Documentation Home](https://tacnode.io/docs): Learn how to build real-time AI applications with Tacnode Context Lake. - [Quick Start](https://tacnode.io/docs/get-started/tacnode-quick-start): Create your first cluster. - [Product Overview (Docs)](https://tacnode.io/docs/get-started/product): Architecture, features, and editions. - [Platform Guides](https://tacnode.io/docs/guides/platform): Cluster management, networking, capacity planning. - [Table Guides](https://tacnode.io/docs/guides/table): Table design, indexes, partitioning, schema evolution. - [Query Guides](https://tacnode.io/docs/guides/query): Query optimization, vector search, full-text search. - [Migration Guides](https://tacnode.io/docs/guides/migration): Migrate from PostgreSQL, MySQL, MongoDB, Elasticsearch. - [SQL Commands Reference](https://tacnode.io/docs/sql-reference/reference/sql-commands): DDL, DML, and utility commands. - [Functions Reference](https://tacnode.io/docs/sql-reference/sql/functions): Built-in functions and operators. - [Data Types Reference](https://tacnode.io/docs/sql-reference/sql/datatype): Supported data types. ## Key Blog Posts - [What Is a Context Lake?](https://tacnode.io/context-lake): Shared context infrastructure for real-time AI agents and decision systems. - [AI Agent Memory Architecture](https://tacnode.io/post/ai-agent-memory-architecture-explained): The three memory layers production AI systems need — episodic, semantic, and state. - [AI Agent Coordination Patterns](https://tacnode.io/post/ai-agent-coordination): 8 production-tested coordination patterns for multi-agent systems. - [Context Drift in AI Agents](https://tacnode.io/post/your-ai-agents-are-spinning-their-wheels): Why agents loop forever on stale data and how to fix it. - [The Ideal Agent Stack for 2026](https://tacnode.io/post/the-ideal-stack-for-ai-agents-in-2026): A vendor-agnostic look at production-grade agent infrastructure. - [Why Real-Time Decisions Fail](https://tacnode.io/post/why-real-time-decisions-fail): Incomplete, inconsistent, and outdated context as root causes. - [Context Silos](https://tacnode.io/post/context-silos): Why AI agents miss knowledge computed elsewhere. - [What Context Engineering Actually Means](https://tacnode.io/post/what-context-engineering-actually-means): Beyond RAG — a domain model with episodic, semantic, and state memory. - [Derived Context](https://tacnode.io/post/derived-context): State computed from events that must be current at decision time. - [What Is Data Freshness?](https://tacnode.io/post/what-is-data-freshness): Definition, metrics, and why stale data silently breaks AI systems. - [Data Freshness vs Latency](https://tacnode.io/post/data-freshness-vs-latency): Fast queries on stale data are dangerous. - [Feature Freshness Explained](https://tacnode.io/post/feature-freshness-explained): Why model accuracy drops in production. - [Retrieval Patterns for AI Agents](https://tacnode.io/post/retrieval-patterns): Exact and semantic retrieval used together — point lookups, joins, aggregations, similarity. - [Similarity Search](https://tacnode.io/post/similarity-search): Embeddings, ANN indexes, and hybrid search — and why separate vector databases create traps. - [LLM Agents: From POC to Production](https://tacnode.io/post/llm-agents-complete-guide): The 4 components of every LLM agent and infrastructure challenges. - [Semantic Operators](https://tacnode.io/post/semantic-operators-llm-sql): Run LLM queries directly in SQL — classify, summarize, and extract data. - [Time Travel Queries](https://tacnode.io/post/time-travel-queries): Undo deletes, debug issues, audit changes with SQL. - [Full-Text Search in PostgreSQL](https://tacnode.io/post/full-text-search-postgresql-complete-guide): tsvector, tsquery, trigram matching, and relevance ranking. - [What Is an Online Feature Store?](https://tacnode.io/post/what-is-an-online-feature-store-definition-architecture-use-cases): Architecture and how it prevents training-serving skew. - [ClickHouse JOINs Are Slow](https://tacnode.io/post/clickhouse-joins-slow-why-how-to-fix): Why columnar databases struggle with JOINs and when to consider alternatives. - [What Is Stale Data?](https://tacnode.io/post/what-is-stale-data): How to detect and prevent stale data. - [What Is Data Observability?](https://tacnode.io/post/what-is-data-observability): Monitor data health across pipelines. - [What Is a Data Contract?](https://tacnode.io/post/what-is-a-data-contract): Structure, format, and quality expectations for data exchanged between systems. ## Company - [About Tacnode](https://tacnode.io/company): Company background and team. - [Careers](https://tacnode.io/company/careers): Open roles at Tacnode. - [Book a Demo](https://tacnode.io/book-a-demo): Schedule a conversation with the Tacnode team. - [Press](https://tacnode.io/press): Press coverage and announcements. - [Sign In](https://tacnode.io/signin): Access the Tacnode app. ~~~ ## llms-full Not found.