The AI knowledge backend for the enterprise.
Not a generic chatbot. Kepler is knowledge infrastructure — reliable, auditable, built to operate quietly in real production environments.
Built for daily operations, not for demos.
Most AI chatbots are designed for demos, not daily operations. They hallucinate, go off-brand, and break down under real business requirements.
Kepler is different. It's built as knowledge infrastructure — predictable, secure, and suitable for organizations that need AI they can trust in production.
Data Augmented Generation Architecture.
The pipeline for transforming organizational data into secure, searchable AI knowledge.
Stage 01
Data ingestion
Secure ingestion from documents, policies, websites, contracts, and internal resources with enterprise-grade encryption.
- · Multi-source data collection
- · Automated document parsing
- · Secure data validation
Stage 02
Processing pipeline
Advanced chunking, embedding, and indexing using state-of-the-art ML models optimized for enterprise knowledge.
- · Semantic embeddings
- · Context-aware chunking
- · Vector database storage
Stage 03
Retrieval generation
Precision retrieval with source attribution. Responses grounded only in your approved content.
- · Source-grounded responses
- · Citation tracking
- · Confidence scoring
Enterprise-grade infrastructure.
Deployed on AWS, engineered to meet enterprise infrastructure and security standards. Purpose-built for organizations that require secure, compliant, scalable data pipelines.
Isolated deployments
Dedicated infrastructure per organization — your data never mingles with others.
Auto-scaling architecture
Handles spikes in usage seamlessly with elastic compute resources.
99.9% uptime SLA
Production-grade reliability with monitoring and automated failover.
- Cloud provider
- Amazon Web Services (AWS)
- Compute
- Elastic Container Service (ECS)
- Database
- Vector DBs + RDS PostgreSQL
- Authentication
- SSO, OAuth 2.0, SAML
- Encryption
- AES-256 at rest, TLS 1.3 in transit
- Monitoring
- CloudWatch, custom alerting
Designed for daily business operations.
Response time
Fast retrieval from millions of document chunks.
System uptime
Reliable infrastructure with automated monitoring.
Source grounded
Every response cites approved organizational content.
Scaling
Handles concurrent users at any load.
Built for regulated industries.
Stringent security requirements for organizations that can't compromise.
01
SOC 2 ready
Infrastructure designed to support SOC 2 Type II compliance.
02
SSO integration
Seamless integration with enterprise identity providers (Okta, Azure AD).
03
Private cloud
Isolated deployment per customer. Your data stays in your dedicated environment.
04
Audit logs
Comprehensive logging and monitoring for compliance audits and reviews.
From your data to intelligent answers.
A secure, auditable pipeline.
- Step 01
Your data sources
Documents, policies, websites, contracts, and internal resources collected securely with enterprise-grade encryption. - Step 02
DAGA processing
Content is chunked, embedded, and indexed using ML models optimized for your knowledge base. - Step 03
Natural language query
Users ask questions in plain English through a clean, intuitive interface designed for daily use. - Step 04
Grounded response
AI retrieves relevant content and generates accurate answers with source citations — no hallucinations.
Common questions about Kepler.
What technical buyers ask during architecture review.
01What is Kepler?
Kepler is enterprise AI knowledge infrastructure built by Seattle AI Developers. It ingests organizational data, indexes it for retrieval, and powers grounded AI responses for both internal teams and customer-facing interfaces.
02What is DAGA?
DAGA — Data Augmented Generation Architecture — is the ingestion pipeline behind Kepler. It handles secure data collection, semantic chunking, vector embedding, and indexing so AI responses are grounded in approved organizational content.
03Where is Kepler deployed?
On Amazon Web Services, in dedicated infrastructure per customer. Compute runs on ECS, vector storage is paired with RDS PostgreSQL, and the deployment uses isolated VPCs so no data crosses tenant boundaries.
04Is Kepler SOC 2 compliant?
The infrastructure is SOC 2 ready and designed to support SOC 2 Type II compliance. Encryption (AES-256 at rest, TLS 1.3 in transit), SSO via Okta or Azure AD, and comprehensive audit logging are standard.
05What is the typical response time?
Under two seconds end to end, including retrieval from millions of document chunks and generation of the grounded response. Auto-scaling handles concurrent users without queueing.
06Can Kepler integrate with our existing tools?
Yes. Common integrations include Slack, Microsoft Teams, internal portals, and SaaS tools via API. The system also exposes REST endpoints so it can power any custom interface you already operate.
Ready to see Kepler in action?
Let's talk about how the infrastructure powers your AI knowledge systems.