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//Production AI Engineering

AI and LLM Integration Services

We bring large language models into your existing application or product workflow. Custom RAG pipelines, fine-tuned models, intelligent document processing, and production-ready AI features, built with security, rate limits, and latency budgets in mind.

What We Build

Retrieval-Augmented Generation (RAG) Pipelines

Connect LLMs to your proprietary data (PDFs, databases, internal wikis, or support knowledge bases) so your users get accurate, context-aware answers without hallucinations.

AI Chatbots and Conversational Agents

Custom-built chatbots embedded into web and mobile products. Designed around specific business roles: customer support, lead qualification, or internal HR assistance.

Document Intelligence and Data Extraction Systems

Automate document processing (invoices, contracts, legal filings, CVs, or receipts) using multimodal AI that extracts structured data into your database.

LLM-Powered Feature Layer for SaaS

Add AI capabilities to an existing product: text summarisation, automated tag generation, content drafting, translation, or smart search.

Custom API Wrappers and Middleware

Secure, production middleware that handles model routing, rate limiting, response caching, token usage tracking, and fallback handling across OpenAI, Claude, and Gemini.

Which AI Model Is Right for Your Project

We match models to requirements, balancing cost, latency, capability, and data privacy.

OpenAI (GPT-4o, GPT-4o-mini)

Best for general reasoning, complex instruction following, code generation, and applications needing vision capabilities. The default choice for most SaaS AI features.

Anthropic (Claude 3.5 Sonnet, Claude 3 Opus)

Best for long-context analysis (up to 200k tokens), complex document processing, legal and financial text extraction, and tasks requiring high safety and nuanced writing.

Google (Gemini 1.5 Pro, Gemini Flash)

Best for large context windows, cost-effective high-volume processing, multimodal audio/video understanding, and native Google Cloud infrastructure integration.

Open-Source Models (Llama 3, Mistral)

Best for businesses that require full data privacy, local or on-premises deployment, zero third-party API reliance, or fine-tuning on proprietary datasets.

What Every Delivery Includes

Production-tested API endpoints with error handling and fallback routing.
Vector database configuration (Pinecone, Qdrant, or pgvector).
Token usage tracking dashboard to monitor API consumption and costs.
Comprehensive integration documentation and API schema.
Milestone Scoping & Quote Engine

Request a Milestone Quote for AI and LLM Integration

Submit your specific technical requirements, feature wish-list, or existing product links. We evaluate the scope and provide a fixed-price timeline estimate within 4 business hours.

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Average response time: < 4 Business Hours
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Frequently Asked Questions

No. We configure all API connections using enterprise-grade commercial terms, ensuring your data remains private and is never used for foundation model training.

Have a Specific Question?

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//Ready to Build Something Production-Grade?

Turn Your Requirements Into a Fixed-Price Quote

Schedule a free 30-minute technical discovery call with our engineering lead. We inspect your scope, establish milestones, and lock in your price tag before writing code.

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100% IP Code Ownership
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