Question 1

What kinds of AI products does OutGrow build?

Accepted Answer

OutGrow builds AI-native software including LLM-powered applications (chatbots, document Q&A systems, AI assistants), RAG (Retrieval-Augmented Generation) pipelines, intelligent data processing tools, AI-powered internal tools, customer-facing AI features, and fully custom AI SaaS products. We work from concept through production deployment, with full code ownership transferred to clients.

Question 2

How long does it take to build an AI product with OutGrow?

Accepted Answer

A focused MVP with 2–3 core AI features typically takes 6–12 weeks from kickoff to production deployment. More complex products with multiple AI workflows, fine-tuned models, and enterprise integrations typically run 3–6 months. We deliver in fortnightly sprints with working software at each milestone.

Question 3

Which LLMs does OutGrow use — GPT-4, Claude, or open-source models?

Accepted Answer

We use the best model for each specific task. GPT-4 and GPT-4o for general reasoning, document analysis, and customer-facing chat. Claude for long-context document processing and nuanced writing tasks. Open-source models (Llama, Mistral, Phi) for on-premise deployments or cost-sensitive inference at scale. We never lock clients into a single provider — architecture decisions are driven by cost, accuracy, and latency requirements.

Question 4

What is a RAG pipeline and when does my business need one?

Accepted Answer

RAG (Retrieval-Augmented Generation) is an architecture that lets an LLM answer questions using your proprietary documents, databases, or knowledge bases — rather than relying only on its training data. You need a RAG pipeline if you want AI to answer questions about your products, contracts, manuals, customer data, or internal policies accurately without hallucinating. OutGrow has built RAG systems for legal firms, real estate developers, and SaaS companies.

Question 5

Do we own the code and models OutGrow builds?

Accepted Answer

Yes — completely. Full source code, model weights (for fine-tuned models), training data pipelines, and infrastructure configurations transfer to you at project close. We do not retain any IP, we do not require ongoing retainers to keep the product running, and we do not build on proprietary OutGrow platforms. Everything is built on open standards.