Real World Production Ready

Use Cases

From individual developers to global enterprises, see how Eldric transforms AI workflows.

For Developers

Train a Codebase-Specific AI Assistant

Eldric Client • Solo Developer / Small Team

Create an AI that deeply understands your specific project, coding conventions, and architecture decisions.

The Challenge

  • Generic AI doesn't know your codebase
  • Constantly re-explaining context
  • Wrong suggestions that don't match your patterns
  • Can't ask "how do we handle auth here?"

The Solution

  • Fine-tune on your codebase (LoRA/QLoRA)
  • AI learns your naming conventions
  • Understands your architecture decisions
  • Answers project-specific questions accurately

Workflow

# 1. Prepare training data from your codebase eldric> /train prepare ./src --output training-data.jsonl # 2. Fine-tune a model on your code eldric> /train create --base llama3.1:8b --data training-data.jsonl --epochs 3 # 3. Use your custom model eldric> /model my-codebase-expert eldric> How does authentication work in this project? AI: Based on your codebase, you use JWT tokens with refresh rotation. The auth middleware is in src/middleware/auth.ts, and tokens are validated using the verifyToken() function from src/utils/jwt.ts...
85%
Less Context Needed
3x
Faster Onboarding
100%
Private

Build a Private Knowledge Base

Eldric Client • Documentation & Internal Wikis

Turn your company documentation, runbooks, and tribal knowledge into a searchable AI assistant.

What You Can Index

  • Internal documentation (Confluence, Notion exports)
  • Runbooks and playbooks
  • Architecture decision records
  • Meeting notes and design docs
  • API documentation

What You Get

  • Instant answers from your docs
  • Semantic search (meaning, not keywords)
  • Source citations for every answer
  • Always up-to-date (re-index anytime)
  • Zero training required

Workflow

# Index your documentation eldric> /learn ./company-docs --recursive [Learn] Indexing 847 documents (312 MB)... [Embed] Creating vectors with nomic-embed-text... [Done] Knowledge base ready! 12,456 chunks indexed. # Ask questions eldric> What's our incident response process for P1 issues? AI: Based on your runbooks (incident-response.md): 1. Acknowledge in #incidents Slack channel within 5 minutes 2. Page on-call engineer via PagerDuty 3. Create incident ticket with template from JIRA 4. Begin investigation, update every 15 minutes 5. Post-mortem required within 48 hours [Source: docs/runbooks/incident-response.md, lines 23-45]

Merge Models for Specialized Tasks

Eldric Client • Advanced Users

Combine the strengths of multiple models into one custom model optimized for your workflow.

Example Merges

  • Code model + Reasoning model = Better code reviews
  • Base model + Your LoRA = Domain expertise
  • Fast model + Accurate model = Balanced performance
  • English model + Multilingual = Global support

Merge Strategies

  • SLERP: Smooth blending (recommended)
  • TIES: Preserves unique capabilities
  • DARE: Randomized for diversity
  • Linear: Simple weighted average

Workflow

# Create a merged model eldric> /merge create Select models: 1. codellama:13b (code generation) 2. mistral:7b (reasoning) 3. my-domain-lora (your expertise) Strategy: SLERP Weights: 0.4 / 0.3 / 0.3 [Merge] Processing tensors... [Done] Created: my-code-reasoning-expert (14.2 GB) # Your merged model combines all three capabilities

For Teams

Shared AI Infrastructure for Development Team

Eldric Multi-API • 10-50 Developers

Deploy a shared AI cluster that your entire team can use without individual GPU requirements.

Setup

  • 1 management server (Controller + Router)
  • 2-5 GPU workers (existing workstations)
  • Optional: Edge server for OpenWebUI
  • Models: llama3.1:70b, codellama:34b

Benefits

  • No GPU needed on developer laptops
  • Shared access to large models (70B+)
  • Centralized model management
  • Usage tracking per developer
  • Works with existing tools (Cursor, Continue)

Architecture

Developer Laptops GPU Workstations Cursor IDE Continue IDE Management Server Controller (8880) Router (8881) Edge (443) optional Worker 1 RTX 4090 llama3.1:70b Worker 2 RTX 3090 codellama:34b # Developers point their tools at the router OPENAI_API_BASE=http://mgmt-server:8881/v1
$0
Cloud API Costs
70B
Model Size Access
<50ms
Local Latency

OpenWebUI for Non-Technical Teams

Eldric Multi-API + Edge Gateway

Give marketing, sales, and support teams access to AI via a friendly web interface.

Setup

  • Eldric cluster (Controller + Router + Workers)
  • Edge gateway with TLS certificate
  • OpenWebUI connected to edge
  • Per-team API keys with rate limits

Use Cases

  • Marketing: Content generation, copy editing
  • Sales: Email drafts, proposal summaries
  • Support: Response templates, FAQ answers
  • HR: Job descriptions, policy summaries

Setup Commands

# Deploy edge with TLS ./eldric-edge --port 443 \ --cert /etc/ssl/company.pem --key /etc/ssl/company.key \ --routers http://router:8881 # Register team clients with different limits curl -X POST https://ai.company.com/api/v1/clients/register \ -d '{"name": "Marketing Team", "rate_limit_rpm": 500}' # Returns: api_key: eld-marketing-xxx curl -X POST https://ai.company.com/api/v1/clients/register \ -d '{"name": "Sales Team", "rate_limit_rpm": 1000}' # Returns: api_key: eld-sales-xxx # Configure OpenWebUI OPENAI_API_BASE_URL=https://ai.company.com/v1 OPENAI_API_KEY=eld-marketing-xxx

For Enterprise

Multi-Region AI Deployment

Eldric Multi-API • Global Enterprise

Deploy AI infrastructure across multiple regions with data sovereignty, failover, and geo-routing.

Requirements Met

  • GDPR: EU data stays in EU
  • Low latency: Route to nearest region
  • High availability: Auto-failover
  • Compliance: Region-specific models
  • Cost optimization: Right-size per region

Architecture

  • Primary Controller: US-West (orchestration)
  • Secondary Controller: EU-West (autonomous)
  • Secondary Controller: APAC (autonomous)
  • Each region: Local routers + workers
  • Global edge farm with geo-routing

Global Architecture

Global Load Balancer US-West Primary Controller Port 8880 EU-West Secondary Controller Port 8880 APAC Secondary Controller Port 8880 sync sync Router + Workers 10 GPU Port 8881 / 8890 Router + Workers 5 GPU Port 8881 / 8890 Router + Workers 3 GPU Port 8881 / 8890 • EU users → EU workers (GDPR compliant) • US users → US workers (lowest latency) • Failover: If region down, route to nearest healthy
99.99%
Uptime
<50ms
Regional Latency
100%
Data Sovereignty

AI-Powered Customer Support Platform

Eldric Multi-API • High-Volume Production

Handle millions of customer inquiries with intelligent routing, RAG-powered responses, and human escalation.

Components

  • Edge farm: Handle incoming requests
  • Fast workers: Quick responses (llama3.2:3b)
  • Quality workers: Complex queries (llama3.1:70b)
  • RAG: Product docs, FAQ, past tickets
  • AI routing: Match query to best model

Flow

  • 1. Customer sends inquiry
  • 2. AI classifies: simple/complex/escalate
  • 3. RAG retrieves relevant docs
  • 4. Route to appropriate model
  • 5. Generate response with citations
  • 6. Log for training/improvement

Request Flow

Customer: "How do I reset my password?" [Edge] Received request, rate limit OK [Router] AI classification: SIMPLE_FAQ [Router] Selected: worker-fast-01 (llama3.2:3b) [Worker] RAG search: "password reset" → 3 relevant docs [Worker] Generated response with citations Response: "To reset your password: 1. Go to login page and click 'Forgot Password' 2. Enter your email address 3. Check your inbox for reset link (expires in 1 hour) 4. Click link and create new password [Source: help-center/account/password-reset.md]" Latency: 145ms | Tokens: 89 | Cost: $0.00003
10M+
Queries/Month
92%
Auto-Resolved
$0.02
Per 1K Queries

By Industry

Healthcare

HIPAA-compliant clinical documentation, triage assistance, and medical research summarization. Air-gapped deployment available.

  • • Clinical note generation
  • • Patient triage support
  • • Research paper analysis

Financial Services

Fraud detection, regulatory compliance analysis, and trading signal generation with sub-10ms latency requirements.

  • • Real-time fraud scoring
  • • Compliance document review
  • • Risk assessment

Legal

Contract analysis, legal research, and document review with attorney-client privilege protection.

  • • Contract clause extraction
  • • Case law research
  • • Due diligence automation

Manufacturing

Predictive maintenance, quality control, and supply chain optimization with edge deployment.

  • • Equipment failure prediction
  • • Defect detection
  • • Process optimization

Education

Personalized tutoring, automated grading, and curriculum development with student privacy.

  • • Adaptive learning paths
  • • Essay feedback
  • • Content generation

Government

Citizen services, document processing, and policy analysis with FedRAMP-ready architecture.

  • • Form processing
  • • Policy summarization
  • • Public records analysis

Eldric vs. Alternatives

Feature Cloud APIs Self-Hosted (Manual) Eldric
Data Privacy Data leaves your network Full control Full control
Setup Time Minutes Days/Weeks Minutes
Cost at Scale $$$$ (per token) Fixed hardware Fixed hardware
Custom Training Limited Complex setup Built-in
Multi-Region Yes DIY orchestration Built-in
Load Balancing Managed DIY Built-in + AI routing
Vendor Lock-in High None None (25+ backends)

Ready to See Eldric in Action?

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