Our Solutions
We manage all backend components, including LLM integration for digital products, using top-tier models like OpenAI's GPT-4 or Anthropic’s Claude. Based on your compliance and performance needs, we can also integrate open-source LLMs such as Mistral or LLaMA. Whether it’s an in-app chatbot or backend automation, our AI integration is always secure and contextual.
To enable memory and search, we implement vector databases that convert your company’s documents and product data into embeddings. This fuels intelligent semantic search far beyond keyword matching. As an enterprise AI embedding solution, we support both scalable cloud options like Weaviate and fast in-app tools like Faiss.
We craft reusable prompt templates tailored to specific workflows — from user assistance and content summarization to support deflection. These prompts are deeply integrated into your frontend stack (React, Vue, etc.), providing a fluid UX. This is how we help augment software with generative AI while staying on-brand and responsive.
Our instrumentation setup includes logging model latency, success/failure rates, user feedback, and interaction heatmaps. With prompt chain traceability, we enable fast iteration, reduced hallucinations, and clear analytics — a crucial part of AI-driven automation for business tools that need real-time insights.
- RAG Pipeline Implementation Agency for Contextual AI
Using retrieval-augmented generation (RAG), our assistants provide answers grounded in your actual files — from PDFs and internal wikis to product manuals. As a RAG pipeline implementation agency, we ensure precision with custom chunking, tuned embeddings, and real-time grounding for source-backed answers.
- Agent Workflows
Modern AI doesn’t just answer — it acts. We implement agents that proactively resolve tickets, trigger actions in your app, and summarize CRM data. These AI agents are traceable, safe, and designed for AI-driven automation for business tools, streamlining workflows without compromising governance.
- Fine-Tuning and Customization
In verticals like finance, legal tech, and healthcare, off-the-shelf models often miss the mark. We offer domain-specific fine-tuning on GPT-3.5 and open-source models using your datasets and transcripts, enabling enterprise AI embedding solutions that reflect your tone, terminology, and compliance requirements.
- Frontend UI & Branding
We believe AI integration services for SaaS should feel native. Our design team builds tailored UI components like floating copilots, command palettes, and context-aware tooltips. These components work across React, Vue, or custom stacks — blending GPT power with your unique brand experience.
Questions
& Answers
Most clients go live within 3–6 weeks, depending on the complexity of the integration. Our standard package is designed for speed — with battle-tested templates, pre-built components, and a phased rollout plan. We start with a scoping call, align on data sources and use cases, and begin implementation immediately. Add-ons like RAG ingestion or agent workflows may add 1–2 additional weeks, but we keep the entire process agile and milestone-driven.
Yes — securely and intelligently. With our vector database integration and optional RAG add-on, we enable your assistant to ingest and semantically search internal documents, wikis, and structured data. You control exactly what’s included, how it’s chunked, and how it’s surfaced in responses. Nothing is exposed to external LLM providers unless explicitly configured. We prioritize data privacy and compliance at every stage.
No, and that’s the point. Our service is designed for product, engineering, and ops teams who want to embed AI without spinning up internal ML infrastructure. We provide the architecture, model integration, analytics, and prompt design — all packaged into a managed setup. After go-live, you can either self-manage with our guidance or retain us for continued support and iteration.
