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Ready to deploy local LLMs and Vector Intelligence? Let's discuss your requirements.
What to Expect
Our proven deployment process from discovery to production
Discovery Call (30 min)
Understand your use cases, data landscape, and infrastructure. Identify quick wins and long-term opportunities.
Technical Assessment (1 week)
Evaluate data quality, model requirements, and integration points. Provide detailed proposal with timeline and costs.
POC Development (2-4 weeks)
Build proof-of-concept with your actual data. Demonstrate accuracy, performance, and ROI potential.
Production Deployment (4-8 weeks)
Full model training, infrastructure setup, integration, and team training. Go-live with ongoing support.
Frequently Asked Questions
What's the minimum data requirement for fine-tuning?
We recommend at least 10,000 high-quality examples for meaningful fine-tuning. For RAG-based systems using vector search, you can start with as few as 100 documents.
How long does deployment typically take?
From initial call to production: 8-12 weeks on average. POC can be ready in 2-4 weeks. Timeline varies based on data complexity and infrastructure readiness.
What infrastructure do I need?
Minimum: 2x GPU servers (NVIDIA A100 or equivalent) for production. We support AWS, Azure, GCP, or on-prem deployment. Edge deployments possible with model quantization.
Can you integrate with our existing systems?
Yes. We provide REST APIs, Python/JS SDKs, and can build custom connectors for your ERP, CRM, or data warehouse. SSO integration supported.
What's the pricing model?
Licensed per environment (dev/staging/prod) with volume-based tiers. Includes model training, deployment, and 12 months support. Contact us for custom quote.
Do you offer ongoing support and updates?
Yes. Enterprise plans include 24/7 support, quarterly model updates, and continuous improvement as your data evolves. SLA guarantees available.