Approach
Superatom’s automated semantic modeling handles what traditional BI tools require consultants to do manually. When a data source is connected, the system:1
Schema Analysis
Analyzes the database schema and profiles the data automatically.
2
Business-Term Mapping
Proposes mappings between database columns and business terms your team actually uses.
3
Queryable Model
Builds a queryable semantic model so teams can start asking questions immediately.
4
Continuous Refinement
Improves through usage and structured feedback as domain experts capture tribal knowledge.
Timeline at a Glance
Core implementation takes 6-8 weeks, with an additional 4-week optimization phase.Phase Overview
Phase 1: Deploy and Connect
Platform running on your infrastructure with initial data sources connected and the Chat Agent answering questions. Power users validate answers against live data.
Phase 2: Build Knowledge and Refine
The semantic model is enriched with organizational context through structured feedback and tribal knowledge capture. Common questions reach high accuracy.
Phase 3: Dashboards, Reports, and Workflows
Operational dashboards, scheduled reports, automated workflows, and mobile access are configured and deployed.
Phase 4: Go-Live and Activation
Full production deployment. Autonomous monitoring is activated. All user groups are onboarded across the organization.
Phase 5: Optimization and Expansion
Performance optimization, expanded use cases, stress testing, and knowledge transfer to your admin team.
Superatom deploys entirely within your infrastructure. No customer data leaves your network. The only outbound connection is HTTPS to the LLM provider, which can be proxied or replaced with a self-hosted model for air-gapped environments.
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Implementation Phases
Detailed breakdown of each phase with deliverables and responsibilities
Infrastructure Requirements
Server specs, network requirements, and deployment options
Timeline & Responsibilities
Week-by-week schedule and what your team provides