1500+ Client Case Studies Proving Our Results-driven Approach
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AI Development Company 

Production-Ready AI Systems Built for Your Business, Not Off the Shelf. 

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Trusted by 1500+ happy clients, including some top fortune 500 companies

What is AI Development?

AI development is the end-to-end process of designing, training, and deploying AI systems that automate decisions, generate insights, and solve complex business problems at scale built around your data, your workflows, and your specific outcomes. 

Built on Modern AI Architecture

LLMs, RAG pipelines, agentic systems, or custom ML models, the architecture is chosen for your use case, not retrofitted from a generic tool. 

Integrated Into Your Stack

Native integration with your ERP, CRM, data pipelines, and third-party APIs, no middleware hacks, no disconnected AI bolted on as an afterthought. 

Owned Entirely by You

Full IP ownership of every model, pipeline, and codebase with zero vendor lock-in, no recurring licensing fees, and complete data sovereignty. 

What Can Sphinx Solutions Build For You? 

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What We Build

AI Development Services 

We build all of it and make sure every system works together. As a trusted AI Development Company in India, Sphinx Solutions engineers bespoke AI solutions across every layer of your business. 

01 Custom AI Solution Development
02 LLM Application Development 
03 Generative AI Development 
04 AI Agent & Agentic AI Development 
05 Machine Learning Model Development 
06 RAG & Knowledge Base Development 
07 NLP & Text Analytics 
08 AI Integration & API Development 
Custom AI Solution Development
Custom AI Solution Development

Creating tailored AI models, such as predictive models for finance or custom neural networks, to solve specific operational challenges.

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LLM Application Development
LLM Application Development

Generic LLM wrappers plateau quickly; we build scalable production apps with memory, tools, retrieval, and guardrails.

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Generative AI Development
Generative AI Development

We develop generative AI systems for content generation, automation, images, code, and compliant optimised outputs.

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AI Agent & Agentic AI Development
AI Agent & Agentic AI Development

We architect autonomous AI agents that plan, execute multi-step tasks, and recover from failures using AutoGen and LangGraph frameworks.

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Machine Learning Model Development
Machine Learning Model Development

We manage data prep, features, training, evaluation, and deployment, ensuring business-specific intelligence tailored.

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RAG & Knowledge Base Development
RAG & Knowledge Base Development

RAG systems delivering accurate, up-to-date AI answers using your data, with an end-to-end pipeline implementation complete.

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NLP & Text Analytics
NLP & Text Analytics

We transform unstructured text using sentiment analysis, entity recognition, classification, multilingual processing, and custom models.

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AI Integration & API Development
AI Integration & API Development

We integrate AI into ERP, CRM, SaaS, and internal tools using high-performance APIs with clear, maintainable documentation for teams.

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What We Solve 

AI SOLUTIONS

We first understand your operational challenge, then design a precise AI solution tailored to your workflows, data, and growth goals, built uniquely for you, not reused from generic or existing use cases. 
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We fine-tune foundation models on your proprietary data so the AI speaks your domain, your terminology, your processes, and your edge cases. The result is a model that outperforms generic alternatives on your specific tasks.
We engineer computer vision systems for image classification, object detection, visual inspection, facial recognition, and document OCR built on TensorFlow, PyTorch, and OpenCV, deployable at the edge or in the cloud.
For clients with strict data governance, compliance requirements, or security mandates, we deploy AI models entirely within your infrastructure, so no data leaves your environment. Full capability, zero cloud dependency.
Before full investment, we build fast, focused AI proofs of concept that validate your use case against real data in 4–6 weeks. You get a working technical demonstration and a clear decision framework for production build.
We add AI capabilities to your existing software without rebuilding it. Intelligent automation layers, predictive modules, and NLP interfaces integrated into legacy systems using a clean API architecture.
We design and implement vector database infrastructure Pinecone, Weaviate, ChromaDB, Qdrant, powering semantic search, recommendation systems, and RAG pipelines with the retrieval performance production systems demand.
We identify the highest-impact automation opportunities in your workflows and build AI-powered automation solutions combining LLM reasoning, structured decision logic, and RPA tooling to eliminate manual processing at scale.

Proof of Work

AI Development Projects That Delivered
Measurable Results

NO STRESS IMPRESS 

AI-Powered Student Productivity & Mental Wellness Platform

  
Problem

Students struggled to balance academics, deadlines, and mental well-being. Existing tools were too generic or lacked personalisation, causing low engagement, poor productivity, and ineffective stress management outcomes.

  
Challenge

TBuild an AI-driven platform that manages tasks and schedules while understanding user behaviour, stress patterns, and productivity gaps, ensuring a simple, engaging, and personalised experience for students.

  
Solution

Developed an AI-powered mobile platform with task planning, mood tracking and behavioural insights, integrating smart recommendations and analytics to enhance productivity, engagement, and consistency.

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KORAS.AI 

  
Problem

JEmail communication lacked simple encryption. Existing solutions required plugins, technical setups, or complex workflows, making secure communication inaccessible, inconvenient, and difficult for everyday users globally.

  
Challenge

Design an AI-powered encryption system working directly within existing email platforms, eliminating the need for installations, integrations, or training while maintaining simplicity, usability, and strong security standards.

  
Solution

Developed an AI-based encryption platform enabling users to secure emails by adding brackets in the subject line, automating encryption, decryption, and key management without disrupting existing workflows seamlessly.

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PROMARKETER.AI

  
Problem

Marketers struggled with managing campaigns across platforms, analysing performance data, and optimising ads in real time. Manual processes led to inefficiencies and missed growth opportunities.

  
Challenge

To create a centralised AI platform that automates campaign management, delivers actionable insights, and continuously optimises marketing performance across multiple channels.

  
Solution

An AI-powered marketing automation system with campaign tracking, audience segmentation and real-time optimisation. Integrated performance dashboards and smart recommendations to maximise ROI.

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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. 

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How We Build It

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.

How We Work

Custom AI Development Process

Our AI development lifecycle follows a structured, outcome-driven methodology built for transparency, speed, and zero architectural surprises. Here’s what happens from your first conversation to your first production deployment and everything after.

STEP 1
Discovery & Use Case Definition

What We Do: We audit your existing systems, map your operational workflows, identify integration dependencies, and produce a detailed Software Requirements Specification (SRS), the single source of truth your entire project builds from.

What You Get:
  • • A clear AI project scope and use case definition.
  • • Data readiness assessment and gap analysis.
  • • Technology recommendations with rationale.
  • • AI development cost estimate and timeline.
STEP 2
Data Strategy & Preparation

What We Do: We analyse your data sources, build scalable pipelines, label data, and set up robust infrastructure because AI performance ultimately depends on the quality of its data.

What You Get:
  • • Data pipeline architecture documentation.
  • • Labelled, cleaned, and structured training datasets.
  • • Data governance and compliance framework.
  • • Ongoing data ingestion strategy.
STEP 3
Model Selection & Architecture Design

What We Do: Our AI architects design system blueprints, select ML methods, choose RAG or fine-tuning, and build infrastructure for the performance and privacy of AI. 

What You Get:
  • • Documented AI architecture blueprint.
  • • Model selection rationale (LLM vs custom ML vs hybrid).
  • • RAG pipeline design or fine-tuning specification.
  • • Security and compliance architecture (GDPR, HIPAA, SOC 2).
STEP 4
Development & Integration

What We Do: Development happens in structured sprints, building AI models, apps, integrating via APIS, and deploying to staging with demo-ready builds for real-time.

What You Get:
  • • Sprint demos with working AI functionality.
  • • Regularly updated product backlog.
  • • Full access to your project management board.
STEP 5
Testing, Evaluation & Safety

What We Do: We perform AI benchmarks, hallucination tests, bias audits, adversarial red-teaming, latency profiling, OWASP LLM 10 scans, and validate ML models on held-out and production data.

What You Get:
  • • Model evaluation reports with accuracy and performance metrics
  • • Bias and safety audit results
  • • Zero critical failures before production deployment
STEP 6
Deployment & CI/CD Pipeline Setup

What We Do: We deploy your AI system on AWS Bedrock, Azure OpenAI, GCP Vertex AI, or on-premise, using containers, Kubernetes, and CI/CD pipelines for zero-downtime updates.

What You Get:
  • • Production-ready AI deployment.
  • • Fully automated model release pipeline.
  • • Infrastructure-as-code documentation via Terraform.
  • • Rollback strategy for model incidents.
STEP 7
Post-Launch Support, Monitoring & Optimisation

What We Do: We deliver L1–L3 support, continuous performance monitoring, periodic retraining as data evolves, and a clear AI roadmap to ensure accuracy, reliability, and business alignment.

What You Get:
  • • SLA-backed response times.
  • • Monthly AI performance health reports.
  • • Model retraining and optimisation schedule.
  • • On-call AI Support Engineer.
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How We Engage

Engagement Models That Fit Your AI Project

As a leading AI development company, we offer three fully transparent engagement models designed to build enterprise AI without surrendering control, IP ownership, or delivery accountability.

Fixed Scope AI Delivery

Fixed-scope, milestone-based billing model perfect for AI PoCs, ML projects, and RAG solutions. It ensures clear deliverables, timelines, and costs, giving you complete budget certainty from start to finish.

Agile AI Development

Billed per sprint hours with a reprioritizable backlog and monthly invoicing, ideal for LLM apps, agentic AI systems, and evolving AI products shaped by user feedback and advancing model capabilities.

Dedicated AI Engineering Team

An AI team embedded in your workflow, including engineers, scientists, and MLOps experts, delivering senior-level AI solutions helping you scale capabilities without building an in-house team from scratch.

Not sure which model fits your AI project stage?

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Who we build for

AI Development Across Industries

Healthcare Technology

We deliver healthcare AI solutions, including clinical decision support, AI diagnostics, patient triage bots, medical document processing, and drug discovery models built to meet HIPAA compliance and the data privacy demands of modern healthcare providers.

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Banking & Financial Services 

We develop AI systems for fraud detection, credit risk scoring, automated compliance monitoring, financial forecasting, and intelligent document processing, engineered to meet regulatory standards and deployed within secure, auditable infrastructure.

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eCommerce & Retail 

Our retail AI solutions include personalisation engines, dynamic pricing systems, AI-powered visual search, demand forecasting, and inventory optimisation built to increase conversion, reduce operational overhead, and improve customer experience at scale.

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Logistics & Supply Chain 

We build logistics & supply chain AI systems for route optimisation, predictive demand forecasting, warehouse automation and supply chain risk modelling, giving logistics operators the intelligence to reduce costs and improve fulfilment reliability.

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HR & Recruitment

Our HR AI solutions include intelligent resume screening, candidate-role matching engines, employee sentiment analysis, and workforce planning models, replacing high-volume manual tasks with AI systems that improve quality and speed of hire.

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Manufacturing 

We develop manufacturing AI systems for predictive maintenance, computer vision-based quality inspection, production process optimisation, and defect classification, reducing downtime and quality escapes in manufacturing environments.

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Media & Entertainment

We build media & entertainment AI systems for content recommendation, automated content tagging, generative content tools, audience intelligence, and personalisation engines, helping media companies deliver relevant experiences at scale.

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Education & EdTech 

Our education AI solutions include adaptive learning systems, AI tutors, automated assessment tools, and student performance analytics, helping institutions deliver personalised, data-driven learning experiences at any scale.

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  • Healthcare
  • Banking & Financial Services 
  • eCommerce & Retail 
  • Logistics & Supply Chain 
  • HR & Recruitment
  • Manufacturing 
  • Media & Entertainment 
  • Education & EdTech 

Why Choose Us

Client-Oriented. On-Time Delivery

15+ years of experience

Sphinx has completed 15 successful years in the industry by helping businesses with technology and digital transformation, including AI-powered solutions in major industry vertical. 

15+ Industry Experts

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

1500+ Solutions Delivered

We have successfully delivered 1500+ solutions to our clients through our results-driven approach, many of them being recurring clients who expand their AI capabilities with us.

200+ In-House Resources

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

750+ Happy Clients

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

50+ Million Users Love Our Work

Our client-centric approach and high-calibre AI engineering, leveraging the latest models and frameworks, have made us a trusted partner for businesses building AI.

Partner with Experts Who Turn AI into Business Value See How AI Can Transform Your Operations.

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faq

Frequently Asked Questions

AI development is the process of designing, training, and deploying AI systems, including machine learning models, large language model applications, generative AI tools, computer vision systems, and autonomous AI agents built to automate decisions, process unstructured data, and solve complex business problems. Custom AI development means the system is trained on your data, integrated with your infrastructure, and optimised for your specific business outcomes.

AI development costs vary significantly by scope and complexity. An AI Proof of Concept (PoC), mid-tier LLM application, RAG system, or custom ML solution includes important integrations, and the primary cost drivers are model selection, data preparation requirements, number of integrations, compliance standards, cloud infrastructure, and ongoing monitoring and retraining. We have also provided the option of “AI Cost Calculator”.

A well-scoped AI PoC typically takes 4–6 weeks from discovery to demonstration. A production LLM application or RAG system with integrations takes 8–16 weeks. Custom ML model development, including data preparation and MLOps infrastructure, typically takes 4–9 months. Enterprise AI platforms with multi-model orchestration, compliance architecture, and full deployment pipelines generally require 9–18 months end-to-end.

Traditional software follows explicit, pre-programmed rules; it does exactly what developers instruct it to do. AI development takes a fundamentally different approach: instead of writing rules, we train models on data so the system learns patterns and makes predictions or decisions autonomously. This means AI systems can handle ambiguous inputs, improve over time with new data, and tackle problems that would be impractical to hard-code, such as understanding natural language, recognising images, detecting fraud patterns, or predicting customer behaviour.

We work with both. Our team selects the right model based on your use case, data privacy requirements, budget, and performance needs. For clients with strict data governance requirements, we deploy open-source models like Llama 3 or Mistral on private infrastructure so data never leaves your environment. For clients prioritising capability and speed-to-market, we leverage GPT-4o, Claude, or Gemini via secure API integrations. We also offer fine-tuning services to customise any model on your proprietary data for domain-specific performance.

Data privacy is built into our AI development process from day one. For sensitive industries like healthcare or finance, we work with anonymised or synthetic data during development, implement role-based access controls, and can deploy models fully on-premise or in a private cloud environment, so data never leaves your infrastructure. We follow SOC 2-aligned practices and can operate within GDPR, HIPAA, or other relevant compliance frameworks depending on your region and industry. Every AI system we deploy includes access logging, audit trails, and security review before production release.

We work with both startups and enterprises, and our engagement models are designed to fit each stage. For startups and scale-ups, our fixed-scope AI PoC and MVP delivery model provides budget certainty and fast time-to-market. For enterprises, our dedicated AI engineering team model provides the depth of capability, compliance rigour, and integration complexity that large organisations require. The right engagement depends on your project stage, not your company size.

We define ROI metrics at the discovery stage, before development begins. Depending on your use case, these typically include time saved on manual processes, reduction in error rates, improvement in conversion or retention, cost per transaction reduction, or revenue generated through AI-powered features. At post-launch, we run a 90-day performance review measuring actual outcomes against the benchmarks agreed during discovery, giving you a clear, quantified view of what the AI investment has delivered.