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Generative AI Development

Generative AI Development Services

Build secure, scalable, and intelligent AI applications

Generative AI Development Services enable businesses to build AI-powered products using LLMs, RAG, and AI agents. At Foresience, we deliver custom solutions that fit your workflows and technology stack.

GenAI projects delivered

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LLM platforms integrated

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Average time to production

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IP owned by the client

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What We Build

Generative AI Development Services

End-to-end AI development from architecture and model selection through integration, deployment, and ongoing optimisation.

Create AI chatbots and virtual assistants that answer questions, automate support, and improve customer and employee experiences.

Build Retrieval-Augmented Generation (RAG) systems that deliver accurate answers using your business documents and knowledge base.

Develop AI agents that automate repetitive tasks, connect with business tools, and streamline everyday operations.

Integrate leading large language models into your applications to add intelligent features and natural language capabilities.

Build AI applications that understand and process text, images, audio, and documents from a single platform.

Plan the right AI solution with expert guidance on use cases, architecture, technology selection, and implementation.

Customize AI models with your business data to improve accuracy, performance, and domain-specific responses.

Enable fast and accurate semantic search using embeddings and vector databases for better information retrieval.

Implement security controls and AI guardrails to build reliable, compliant, and trustworthy AI applications.

Not sure which service fits your requirements?

Book a free 30-minute call with one of our AI engineers.

Use Cases

What Businesses Build with Us

Our Generative AI Development Services help businesses automate processes, improve customer experiences, and build intelligent AI-powered products across industries.

Customer Support Automation

Deploy AI agents that handle customer queries, automate support tickets, and deliver instant, accurate responses using your business knowledge.

Document Intelligence

Extract, summarize, and search information from contracts, invoices, reports, and other business documents with greater speed and accuracy.

Clinical & Healthcare AI

Build AI assistants for medical documentation, patient intake, clinical support, and healthcare record summarization while supporting compliance requirements.

Content Generation

Generate product descriptions, marketing content, blogs, emails, and SEO copy at scale while maintaining a consistent brand voice.

Internal Analytics Assistants

Enable teams to ask business questions in natural language and receive instant reports, summaries, and actionable insights.

AI-Powered Developer Tools

Improve software development with AI tools for code reviews, documentation, test case generation, and developer assistance.

How We Work

From Idea to Production in Weeks

A structured delivery process designed for AI projects, where requirements evolve, models require evaluation, and production reliability is non-negotiable.

1

Define the use case, success metrics, data availability, model options, and technical constraints.

2

Design the AI pipeline including model selection, retrieval strategy, tool integrations, and infrastructure plan.

3

Develop the core AI system with prompt engineering, vector indexing, API connections, and user interface.

4

Run structured evaluations, test edge cases, reduce hallucinations, and fine-tune for accuracy and consistency.

5

Production deployment with logging, latency monitoring, cost tracking, and a plan for ongoing iteration.

Ready to scope your project?

Get a project estimate in 48 hours

Technology

Our Generative AI Tech Stack

We work across all major LLM providers, frameworks, vector databases, and cloud platforms to recommend the right combination based on your use case, data sensitivity, and budget.

LLM Providers

AN

Anthropic Claude

OP

OpenAI GPT-4o

MI

Mistral

ME

Meta Llama

AZ

Azure OpenAI

GO

Google Gemini

Frameworks

LA

LangChain

LL

LlamaIndex

FA

FastAPI

CR

CrewAI

AU

AutoGen

HA

Haystack

Vector Databases

AZ

Azure AI Search

QD

Qdrant

PG

Pgvector

CH

ChromaDB

WE

Weaviate

PI

Pinecone

ML & Training

WE

Weights & Biases

ML

MLflow

PY

PyTorch

HU

Hugging Face

VE

Vertex AI

SA

SageMaker

Cloud & Infrastructure

AW

AWS

AZ

Azure

GO

Google Cloud

KU

Kubernetes

DO

Docker

TE

Terraform

Why Foresience

What Makes Our Delivery Different

Many AI projects fail to deliver long-term value due to poor planning, limited evaluation, and scalability challenges. Foresience builds reliable, production-ready AI solutions using proven engineering practices and modern architectures.
Our team develops, tests, and optimizes AI applications with a focus on accuracy, performance, cost efficiency, and long-term scalability.

Structured AI evaluations
Production-ready architectures
Version-controlled prompts
Smart model selection
Cost-optimized deployment
Complete knowledge transfer

Compliance Frameworks

Security & Compliance

Built Secure from the Start

Enterprise AI systems process sensitive business data. Security, privacy, and compliance are integrated into every solution from the architecture stage.

Security Practices

Deployment Options

Best for: Rapid deployment

Best for: Enterprise & regulated industries

Best for: Maximum data control

Frequently Asked Questions

Common questions about our generative AI services

Do you work within our existing technology stack?

Yes. We integrate generative AI capabilities into your existing infrastructure. We recommend tools and frameworks based on your use case, but all final decisions remain with your team.

How do you handle data privacy when working with language models?

We design with data privacy at the architecture level. This includes on-premise model deployment where required, PII redaction prior to any LLM call, and private API deployments such as Azure OpenAI for clients with cloud compliance obligations.

How do you select the right language model for a project?

Model selection depends on your accuracy requirements, cost budget, latency targets, and data sensitivity. We run comparative evaluations during the discovery phase and recommend the most appropriate option, or a combination of models for different tasks within the same system.

How do you prevent hallucinations in production systems?

Through RAG architectures that ground responses in source data, structured output enforcement, citation tracking, confidence scoring, and ongoing evaluation pipelines that identify regressions before they affect users.

How long does it take to move from an initial idea to a working product?

A focused MVP typically takes three to six weeks. The timeline depends on data readiness, integration complexity, and scope. We share a project plan with milestones within 48 hours of completing the scoping call.

Can you take over or improve an existing AI system?

Yes. We regularly audit, refactor, and improve existing RAG pipelines, chatbots, and AI integrations, with a focus on improving accuracy, reducing cost per query, and increasing production reliability.

Who owns the code and intellectual property after the project?

Everything produced during the engagement belongs to your organisation. This includes all code, prompts, fine-tuned models, vector indexes, and system designs. An NDA and IP assignment agreement are signed before work begins.

Generative AI Development Services

Build secure, scalable, and intelligent AI applications

What We Build

Generative AI Development Services

AI Chatbots & Assistants

RAG & Knowledge Systems

AI Agents & Automation

LLM Integration

Multimodal AI Applications

AI Strategy & Consulting

Fine-Tuning & Model Customization

Vector Search & Embeddings

Responsible AI & Guardrails

Not sure which service fits your requirements?

Use Cases