Keewano
NexusAi Summary: Keewano is a database and analytics stack for machine reasoning over complete event sequences. It stores ordered events per entity, layers business semantics on top, and serves grounded answers through MCP, SQL, REST, and analytics tools across local and cloud deployments.
NexusAi Overview
Typical workflow: ingest raw events from Kafka, databases, or data lakes; KeewanoDB keeps each entity’s ordered sequence intact. Analysts or agents query business concepts through the semantic layer. Keewano executes reports or comparisons near the data and returns inspectable results via MCP, SQL, REST, and connected BI tools.
How Keewano Works at Event Scale
Ideal for engineering teams building agentic systems, product analytics groups, risk and ops teams, and data engineers maintaining event-heavy stacks. Use it to power LLM agents with grounded context, explore what caused outcomes, compare millions of sequences for lookalikes, and create durable dashboards without rigid schema modeling. KeewanoDB Local supports evaluation, development, and edge deployments; Cloud serves high-volume, multi-tenant, or production-critical workloads. Teams retain current pipelines and warehouses while gaining a purpose-built sequence store for reasoning.
- Stores each entity’s complete, ordered event sequence for direct, low-latency scanning.
- Maps raw fields to shared business concepts through an integrated semantic layer.
- Runs reports, similarity search, and custom logic beside the record.
- Ingests from Kafka, Postgres, Snowflake, BigQuery, and Parquet or Iceberg lakes.
- Serves answers through MCP for agents, plus SQL, REST, and BI.
Why It Matters
Who It’s For
Start with KeewanoDB Local to evaluate on a laptop or single server. Ingest events from Kafka, Postgres, Snowflake, BigQuery, or Parquet/Iceberg without moving existing systems. Define entities, timelines, and semantic mappings to reflect business concepts. Query via SQL and REST, or wire agents through MCP. Enable Keewano Analytics for reports and ongoing checks. When ready, migrate to KeewanoDB Cloud for managed replication and monitoring, keeping the same data model and interfaces.
NexusAi: Route every question through the complete event record, and answers stay explainable.
Getting Started
Keewano’s differentiator is the contiguous, entity-ordered record coupled with a semantic layer and near-data reasoning. It eliminates reconstruction detours, accelerates sequence comparisons, and keeps every answer explainable. SIMD and optional GPU acceleration cut latency under heavy event volumes. Teams retain existing warehouses and streams while adding a purpose-built sequence store. The result: earlier detection of churn, fraud, or failures, lower model and data movement costs, and agent workflows that stay grounded in what actually happened.
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Keewano
Keewano builds infrastructure for machine reasoning at event scale. The team focuses on contiguous sequence storage, semantic context, and near-data computation with SIMD and optional GPU acceleration. Integrations span MCP, SQL, REST, and popular data platforms and streams.
Keewano is a purpose-built event-sequence database and analytics layer for machine-scale reasoning. Instead of modeling around current state, KeewanoDB stores each entity’s events contiguously and in order, preserving full-fidelity history for direct, low-latency scans. A context layer ties events to entities, timelines, and outcomes; a semantic layer maps raw fields to shared concepts so questions reference business meaning, not column names. Reports, similarity search, and custom logic execute close to the record with SIMD and optional GPU acceleration. The system ingests raw events from existing pipelines—Kafka streams, operational databases like Postgres, data warehouses such as Snowflake and BigQuery, and Parquet/Iceberg lakes—without forcing migration. Results are served through MCP for agents, plus SQL, REST, and BI interfaces. Deployments include KeewanoDB Local for single-machine development and edge use, KeewanoDB Cloud for managed, production workloads, and Keewano Analytics for no-code reporting and monitoring. Teams can ask open-ended questions, compare sequences at scale, and trace every answer back to evidence.
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