Is our private data used to train public models?

Intelligent Solutions

Custom LLM & AI Applications Engineered for Measurable ROI

Deploy domain-specific AI models, retrieval-augmented generation (RAG), and reasoning engines into your software.

The Operational Challenge

Generic AI tools lack domain context, risk data leakage, and produce unreliable hallucinations.

Businesses wanting to leverage AI need private, grounded models connected directly to their private documents and databases with strict guardrails.

✕Hallucinations and ungrounded responses from generic public bots

✕Security and privacy concerns with proprietary client data

✕High token costs and latency in unoptimized AI pipelines

Our Approach

Strategic Value & Architectural Overview

We build production-grade AI applications integrating modern LLMs (OpenAI, Claude) with vector search (pgvector, Pinecone). Our RAG architectures ground AI responses in your verified company data with zero data leakage.

100% Code Ownership

2-Week Agile Sprints

Direct Senior Access

Concrete Deliverables

What We Deliver for AI Application Development

Clear, verifiable technical milestones handed over with complete source code.

Custom LLM Application

Full application with prompt engineering, guardrails, and validation.

Vector Database & Embeddings Setup

Semantic search and document indexing pipeline.

Context Retrieval Pipeline

Accurate information extraction with strict hallucination controls.

Technical Standards

Key Engineering Capabilities & Rigor

Hybrid semantic and keyword search for high retrieval accuracy

Token caching and latency optimization to minimize API costs

Automated fallback handlers and moderation guardrails

Sprint Roadmap

Typical Delivery Workflow for AI Application Development

Predictable bi-weekly sprint milestones with staging links and live reviews.

01Week 1

AI Feasibility & Data Audit

Evaluate use cases, data sources, and model selection.

02Week 2

RAG Pipeline & Embeddings

Index documents and configure vector retrieval.

03Weeks 3–4

App Engineering & Guardrails

Build interface, integration hooks, and moderation.

04Week 5

Evaluation & Launch

Benchmark accuracy, deploy cloud API, and handover.

Recommended Technologies for this Service

PythonFastAPIOpenAI APIPineconepgvectorLangChainNext.js

Complementary Frameworks

Frequently Asked Questions

Key questions regarding our AI Application Development engineering engagements.

No. We use private enterprise API endpoints where data is not used for model training.

Start Your Engagement

Ready to Scope Your AI Application Development Project?

Discuss your architecture, timeline, and deliverables directly with our senior software engineering team.

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Generic AI tools lack domain context, risk data leakage, and produce unreliable hallucinations.

Businesses wanting to leverage AI need private, grounded models connected directly to their private documents and databases with strict guardrails.

✕Hallucinations and ungrounded responses from generic public bots

✕Security and privacy concerns with proprietary client data

✕High token costs and latency in unoptimized AI pipelines

Custom LLM & AI Applications Engineered for Measurable ROI

Generic AI tools lack domain context, risk data leakage, and produce unreliable hallucinations.

Strategic Value & Architectural Overview

What We Deliver for AI Application Development

Custom LLM Application

Vector Database & Embeddings Setup

Context Retrieval Pipeline

Key Engineering Capabilities & Rigor

Typical Delivery Workflow for AI Application Development

AI Feasibility & Data Audit

RAG Pipeline & Embeddings

App Engineering & Guardrails

Evaluation & Launch

Recommended Technologies for this Service

Related Packaged Solutions

AI Customer Support Agents

Frequently Asked Questions

Ready to Scope Your AI Application Development Project?

Custom LLM & AI Applications Engineered for Measurable ROI

Generic AI tools lack domain context, risk data leakage, and produce unreliable hallucinations.

Strategic Value & Architectural Overview

What We Deliver for AI Application Development

Custom LLM Application

Vector Database & Embeddings Setup

Context Retrieval Pipeline

Key Engineering Capabilities & Rigor

Typical Delivery Workflow for AI Application Development

AI Feasibility & Data Audit

RAG Pipeline & Embeddings

App Engineering & Guardrails

Evaluation & Launch

Recommended Technologies for this Service

Related Packaged Solutions

AI Customer Support Agents

Frequently Asked Questions

Ready to Scope Your AI Application Development Project?