Enercore AI
Enercore AI
A shared platform that powers all Enercore AI solutions — Snowflake Cortex services, multi-agent architectures, ML models with SHAP explainability, and enterprise-grade security.
Every solution connects to your Snowflake account and uses Cortex AI services — no data movement, no external API calls, no data leaving your governance boundary.
Natural language to SQL. Ask questions in English and Cortex translates them into precise queries against your Snowflake data — production records, sensor logs, market indices.
Semantic document search and RAG. Search across drilling reports, workover documents, union contracts, market reports, and RTO articles — with context-aware retrieval.
Conversational AI powered by large language models. Maintains context across multi-turn conversations for complex operational inquiries and analysis.
Orchestration layer that combines Analyst, Search, and Complete with ML models — routing queries to the right service and synthesizing multi-source answers.
Each solution deploys specialized AI personas that collaborate to answer complex operational questions — routing between data retrieval, ML interpretation, and real-time monitoring.
Retrieves historical data through Cortex Search and Analyst — answering questions about past events, trends, and patterns across time series.
Interprets ML model outputs and SHAP feature importance — translating statistical predictions into actionable operational recommendations.
Real-time monitoring and alerting — detecting anomalies, ghost cycles, clearance violations, and sensor drift as they happen.
Intent classification and routing — understanding user questions and delegating to the right specialist agent for domain-specific answers.
Every prediction comes with SHAP feature importance — so operators understand not just what the model predicts, but why.
Stuck pipe prediction, skills mismatch detection, demand forecasting, fire risk assessment
Schedule risk prediction, asset health forecasting, ROP optimization
Kick detection, vegetation growth prediction with calibrated probability outputs
Transformer-based satellite change detection with ResNet-50/ViT backbone (26 channels, ~2 sec/tile GPU)
ERCOT load forecasting with CDD, HDD, thermal inertia, and cumulative temperature features (~1% MAPE)
Profit-maximizing chemical pricing balancing margin targets against demand elasticity curves
Org-scoped security, rate limiting, audit logging, and observability — designed for teams that need compliance and reliability at scale.
Org-scoped outbound webhooks with delivery tracking, retry logic, and payload signing.
In-app notification system with provider integration for alerts, events, and status changes.
Clerk-powered authentication with SSO, organization switching, role-based access, and user management.
Credentials isolated in Doppler, API rate limiting via Redis, Arcjet protection, and audit logging on all config changes.
Structured logging, distributed tracing (Grafana Tempo), and error tracking across all platform services.
PostgreSQL 17, Redis 7, SeaweedFS (S3-compatible), MongoDB, Unleash feature flags — all containerized with Docker Compose.
Explore how the shared intelligence layer accelerates deployment of AI-powered solutions across your operations.
AI-powered intelligence for energy, construction, and industrial operations.