Generative AI

Generative AI Development Company

Build intelligent AI that creates, thinks, and delivers. As a generative AI app development company, Sphinx Solutions doesn’t build demos.: We build generative AI systems that automate real workflows, reduce operating costs, and scale with your business.

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  • 16+ years engineering
  • 200+ in-house engineers
  • Secure, scalable AI solutions

Trusted By

750+ happy clients, including top Fortune 500 companies

Overview

What is Generative AI Development?

Generative AI creates original content (text, images, code, audio, and video) by learning patterns from large datasets and producing entirely new outputs from a prompt. Unlike traditional AI that classifies existing data or predicts from a fixed dataset, generative AI actively creates.

Large language models

  • GPT
  • Claude
  • Gemini
  • Llama

Text, code, and reasoning tasks.

Diffusion models

  • Stable Diffusion
  • DALL·E

Image and video generation.

Transformer-based multimodals

  • Gemini
  • GPT

Text, image, and audio together.

Custom generative AI development means building production-grade applications on top of these models: fine-tuned on your proprietary data, integrated into your systems, and governed by the compliance rules your industry demands.

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What We Build

Generative AI Development Services

Some businesses need a custom chatbot on proprietary data. Others need agnostic workflows that operate autonomously. We scope the right approach first, then build with precision.

01

RAG application development

Build AI applications that retrieve information from your business data to generate accurate, context-aware responses while reducing hallucinations. Ideal for knowledge assistants, document search, support bots, and enterprise information retrieval.

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02

LLM fine‑tuning services

Customise pre-trained models like GPT, Llama, or Mistral using your business data to deliver more accurate, domain-specific outputs. We handle training, optimisation, and deployment for high-performing AI models.

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03

AI agent development & agentic AI

Build autonomous AI agents that reason, make decisions, and execute multi-step tasks across systems. Ideal for automating support, research, coding, and complex business workflows with minimal human involvement.

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04

Custom LLM application development

Build tailored LLM-powered solutions like chatbots, copilots, and intelligent search tools integrated with your systems. We choose the right AI models and platforms based on your goals, scalability, and budget.

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05

Multimodal AI development

Build AI solutions that process and generate text, images, audio, and mixed-media data in one system, enabling smarter automation, richer insights, and advanced use cases across industries.

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06

Generative AI consulting & PoC development

Assess AI opportunities, define the right roadmap, and validate ideas with a Proof of Concept before full-scale development. Our generative AI consulting services help you reduce risk and maximise ROI from AI adoption, backed by a team that has scoped and shipped production AI systems across industries.

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What We Solve

Generative AI Solutions

We diagnose the business problem first, then engineer the generative AI solution that addresses it precisely. Our solutions are architected around your data, your workflows, and your compliance requirements.

Build RAG-powered assistants that turn internal documents into instant, accurate answers, helping teams access knowledge faster through natural language search.

Automate extracting, classifying, summarising, and routing documents with generative AI, reducing manual effort and turning days of work into minutes.

Build AI assistants for support, onboarding, and helpdesks that automate repetitive queries, improve response accuracy, and escalate complex issues intelligently.

Develop AI-powered content generation systems to create personalised, brand-aligned, SEO-ready content, reports, and documentation accurately and efficiently at scale.

Build autonomous AI agents that execute workflows, automate tasks, connect systems, and streamline operations with intelligent, action-driven automation.

Deploy secure generative AI models within your private cloud or on-premise infrastructure, ensuring full data privacy, compliance, and control.

What We Work With

Generative AI Model Specialisation

No model is right for every job. These are the ones we build on most often, and the work each one is genuinely the best answer for.

Model Best for
GPT‑4o / GPT‑4 Turbo Complex reasoning, code generation, multimodal tasks
Claude 3.5 Sonnet / Claude 3 Opus Long-context analysis, document processing, precise instruction-following
Gemini 1.5 Pro / Gemini 1.0 Ultra Multimodal applications, 1M token context window, Google ecosystem
Llama 3 / Llama 3.1 On-premise deployment, data privacy, cost-sensitive applications
Mistral Large / Mixtral Private cloud deployment, European data compliance (GDPR)
Phi‑3 Edge deployment, low-latency applications, mobile AI
Stable Diffusion XL / SDXL Turbo Image generation, product visuals, creative content platforms
Talk to our AI architects

How We Build It

Generative AI Technology Stack

Every technology in our AI development stack is chosen for performance, scalability, and long-term maintainability. As an AI software engineering company, we select every model, framework, and piece of infrastructure based on your use case.

  • LangChain
  • LlamaIndex
  • AutoGen
  • Semantic Kernel
  • Haystack

How We Work

Generative AI Development Process

Our generative AI development lifecycle is structured, milestone-driven, and built for production deployment. Here’s exactly what happens from your first conversation to your first live system.

  1. Step 1

    Discovery & use case scoping

    What we do: We assess workflows, identify high-ROI AI opportunities, evaluate data readiness and compliance, and then recommend the right generative AI architecture for your business.

    What you get

    • Scoped AI use case with business case validation.
    • Model recommendation with rationale (open vs proprietary).
    • Data readiness assessment.
    • Compliance risk register (HIPAA, GDPR, SOC 2 as applicable).

  2. Step 2

    Architecture design & model selection

    What we do: Our AI architects design scalable system blueprints covering data pipelines, model infrastructure, retrieval logic, APIs, security, and monitoring before development begins.

    What you get

    • Documented AI architecture with infrastructure diagram.
    • Chosen tech stack with rationale.
    • Data pipeline design.
    • Security and compliance architecture.

  3. Step 3

    Data preparation & model configuration

    What we do: We prepare data, build embedding pipelines, configure vector databases, fine-tune models when needed, and validate outputs against quality benchmarks before deployment.

    What you get

    • Cleaned and structured training and retrieval dataset.
    • Configured vector database with your domain data.
    • Fine-tuning evaluation report, where applicable.

  4. Step 4

    Application development & integration

    What we do: We develop complete AI applications with interfaces, APIs, business logic, and system integrations, delivered through agile sprints with continuous, demo-ready progress.

    What you get

    • Sprint demos with working, testable builds.
    • Full integration with your existing stack.
    • Human-in-the-loop controls where applicable.

  5. Step 5

    Evaluation, safety testing & hallucination mitigation

    What we do: We test AI for accuracy, safety, retrieval quality, tool reliability, and failure recovery, with validation layers, confidence scoring, and human review checkpoints.

    What you get

    • Evaluation report with benchmark scores.
    • Hallucination mitigation architecture documented.
    • Output safety and compliance validation.

  6. Step 6

    Deployment, monitoring & ongoing optimisation

    What we do: Deploy securely on cloud or on-premise with containerised infrastructure, CI/CD automation, and continuous monitoring for performance, latency, model quality, cost, and drift.

    What you get

    • Production deployment with SLA-backed uptime.
    • Live AI monitoring dashboard.
    • Monthly model performance reviews.
    • Retraining and prompt optimisation roadmap.

Case Studies

AI Projects That Delivered Measurable Results

Every solution we build is AI-ready by architecture, so your business grows smarter. We engineer software around the way your business, processes, integrations, and growth targets. We bring years of delivery precision to every project across the world.

The Just Breathe app shown on a phone beside the air purification device

JUST BREATHE

Award-winning control intelligence layer for an air purification platform

Problem

Just Breathe had engineered a nature-inspired indoor air purification device combining lab-cultivated plants, AI airscope™ sensors, and airvision™ air quality analytics. The hardware was award-winning. The gap was the software.

Challenge

They needed a cross-platform IoT app enabling real-time air quality monitoring, remote device control, and actionable insights, built from scratch without existing templates in this space.

Solution

A cross-platform IoT app for web, iOS and Android, integrating AI sensors for real-time air quality monitoring, insights, device control, alerts, energy optimisation, and scalable multi-device deployment.

The No Stress Impress app shown on a phone

NO STRESS IMPRESS

AI-powered dental impression guidance platform

Problem

Users taking dental impressions at home often struggle with errors, low confidence, and repeated submissions, creating friction in the customer journey and operational inefficiencies.

Challenge

No Stress Impress required a digital solution that could guide users step by step, simplify impression capture, and improve submission success rates while delivering a seamless mobile experience.

Solution

An AI-enabled mobile platform with guided tutorials, image capture workflows, submission review, cloud infrastructure, and intelligent assistance to streamline at-home dental impressions.

The Amaze Ads campaign dashboard

AMAZE ADS

AI ad automation platform for Amazon and Walmart

Problem

Marketplace sellers struggled with wasted ad spend, manual campaign optimisation, and lost revenue caused by inventory fluctuations and inefficient advertising management.

Challenge

Amaze Ads needed an intelligent platform capable of automating campaign decisions, improving ad performance, and minimising revenue leakage across marketplace ecosystems.

Solution

An AI-powered ad automation platform with campaign optimisation, smart bid management, performance monitoring, revenue recovery mechanisms, and automated ad intelligence for sellers.

Model Comparison

Generative AI Models Comparison

Choosing the right model is the foundation of a successful generative AI project. Here is how the leading models compare across what they do best, their input and output types, and the enterprise use cases they power.

AI model Best for Input type Output type Enterprise use cases
GPT‑4/5 Text generation & automation Text Text Chatbots, copilots, customer support
Gemini Multimodal reasoning Text, image, video Text, image Enterprise assistants, analytics
Llama Open-source AI applications Text Text Private AI deployments
DALL·E Image generation Text Images Marketing creatives, design
Stable Diffusion Custom image generation Text Images Branding, content creation
Whisper Speech recognition Audio Text Transcription, voice assistants

Sources: OpenAI platform documentation; Google Gemini documentation. Last updated: 5 June 2026

How much does it cost?

Generative AI Development Cost

Generative AI development cost depends on several factors:

  • Base model selection.
  • Fine-tuning data size and quality.
  • Cloud infrastructure.
  • Number of integrations.
  • Compliance requirements.

Not sure how much generative AI development will cost? Our AI Cost Calculator makes it simple. Answer a few quick questions about your idea, features, and platform, and get a realistic estimate instantly, no guesswork.

Try AI cost calculator

How We Engage

Engagement Models That Fit Your AI Project

We offer three fully transparent engagement models, so you can partner with Sphinx Solutions in the way that matches your stage, budget, and desired level of control.

01

GenAI PoC sprint

Designed for enterprises exploring AI feasibility before making a full-scale investment. With a fixed scope, fixed cost, and 4 to 6 week delivery, we build a working prototype along with an architecture blueprint to help validate your idea with confidence.

02

Agile AI build

Designed for product teams building and evolving generative AI applications, this model offers sprint-based delivery, a flexible reprioritisable backlog, and transparent monthly invoicing based on actual hours used.

03

Dedicated AI team

For businesses needing long-term AI expertise, we provide a fully managed, cross-functional team of AI engineers, ML specialists, and DevOps experts embedded into your workflow to accelerate innovation and delivery.

Not sure which model fits your project stage?

Book a 30-minute engagement consultation.

Free consultation

Expert Insights

In our experience, enterprises achieve the fastest ROI from generative AI when they focus on workflow augmentation instead of full automation. The biggest wins usually come from knowledge management, customer support, and document intelligence.
Anand Mahajan CEO, Sphinx Solutions

Industries

Generative AI Across Industries

  • Healthcare We build generative AI solutions for healthcare, including clinical documentation automation, AI-powered patient triage, medical decision support, and intelligent assistants that improve care delivery while supporting compliance and security.
  • Automotive Our generative AI solutions for automotive support predictive maintenance insights, in-vehicle assistants, intelligent diagnostics, and automated workflows that enhance mobility, safety, and connected vehicle experiences.
  • Education We build generative AI solutions for education, including adaptive learning assistants, content generation tools, and AI-powered support systems that create more personalised and scalable learning experiences.
  • Media & Entertainment Our generative AI services for media and entertainment enable content creation, script assistance, personalisation engines, and creative automation tools that accelerate production and audience engagement.
  • Retail & eCommerce Our generative AI solutions for retail support product content generation, personalised marketing, AI-powered customer support, and demand intelligence to improve engagement and drive growth.
  • Travel & Transport We build generative AI solutions for travel and transport, including virtual travel assistants, dynamic itinerary generation, support automation, and intelligent route optimisation to improve customer experiences and operational efficiency.
  • Logistics & Supply Chain We create generative AI solutions for logistics, including shipment communication automation, forecasting support, supplier collaboration tools, and intelligent workflows that improve operational efficiency.

Why Choose Us

Client-Oriented. On-Time Delivery.

16+

Years of experience

Sphinx has completed 16 successful years in the industry, helping businesses with technology and digital transformation, including AI-powered solutions across major industry verticals.

16+

Industry experts

We have a dedicated and reliable team of AI engineers, ML scientists, data engineers, and MLOps specialists covering every role in the AI development lifecycle.

1500+

Solutions delivered

We have delivered more than 1,500 solutions through a results-driven approach, many to recurring clients who keep expanding their AI capabilities with us.

200+

In-house resources

We have a dedicated in-house team, experienced and skilled across AI development, software engineering, QA, DevOps, and cloud infrastructure.

750+

Happy clients

We are trusted by 750+ clients for best-in-class AI solutions at competitive rates, with the delivery accountability enterprise clients demand.

50M+

Users love our work

Our client-centric approach and high-calibre AI engineering, built on current models and frameworks, have made us a trusted partner for businesses building AI.

Highly Rated Across Top Platforms

Connect with us

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  • UAE
  • India

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Frequently Asked
Questions

Everything you need to know about building generative AI with us. Can’t find your answer? Talk to us.

RAG (retrieval-augmented generation) retrieves answers from your documents in real time, while fine-tuning trains a model on your data to change its core behaviour. RAG is faster and better for knowledge bases; fine-tuning is better for domain-specific tone, tasks, or specialised outputs.

The data required depends on your specific AI use case. For RAG-based solutions, existing documents, PDFs, websites, or knowledge bases are often sufficient. Fine-tuned AI models typically need high-quality, labelled training data. Our team performs a comprehensive data readiness assessment to identify gaps and determine exactly what data is needed for successful implementation.

Generative AI enhances business productivity by automating routine and time-consuming tasks, optimising workflows, generating content, and providing intelligent insights for faster decision-making. By reducing manual effort and improving operational efficiency, it enables teams to focus on strategic initiatives, innovation, and higher-value work that drives business growth.

The ROI of a generative AI solution can be measured through improvements such as reduced manual effort, faster content creation, lower support costs, fewer processing errors, and increased revenue from personalised customer experiences. At Sphinx Solutions, we work closely with businesses during the discovery phase to define clear KPIs and track measurable outcomes aligned with their goals.

The timeline varies based on factors such as project scope, feature requirements, data availability, third-party integrations, and model training needs. A basic AI solution may be completed within a few weeks, while more advanced, enterprise-grade applications with custom functionality and complex workflows can take several months to design, develop, test, and deploy.

The cost varies based on several factors, including project scope, the AI models used, integration requirements, customisation levels, data complexity, and deployment environment. Since every business has unique goals and technical needs, we recommend contacting our team for a tailored consultation and a detailed cost estimate.