Sphinx offers businesses AI development services, enabling them to discover high-value opportunities for AI, develop custom AI applications, embed intelligent features in various systems, and scale AI solutions. We are experts in both business strategy and AI, bringing data engineering, software development, and AI expertise together to develop solutions focused on real business outcomes, from generative AI to AI agents, machine learning, natural language processing, computer vision, and AI integration.
AI & Machine Learning Solutions
overview
Build Futuristic AI Solutions That Create Measurable Business Value
Proven Impact by the Numbers
0% Boost
In productivity for clients using AI decision-making
0% Increase
In customer retention, using predictive analytics for churn modelling
4.5 /0
Stakeholder satisfaction scores
0% Success Rate
In the model integration
0X Reduction
In operational downtime via AI-powered predictive maintenance
0% Uptime
In the system and <200ms prediction latency for real-time applications.
0% Sales conversion
lift through recommendation engines in e-commerce
0% Increase
in course completion rates and 30% better knowledge retention in AI-powered platforms
AI Development Services We Offer
Sphinx offers end-to-end AI development solutions to address your technology landscape and business goals, from identifying the best AI opportunity to developing, integrating and optimizing AI solutions for production.
AI Consulting & Strategy
AI Consulting Services include AI readiness assessments, discovery of AI use cases, data assessment, technology selection, feasibility study, solution architecture, and implementation planning. We assist in identifying the right AI solution for every business problem, prioritize projects by value and complexity, and outline the journey from experimentation to production.
Custom AI Solutions
Create smart applications that focus on your business processes, data, users and technology landscape. AI Application, AI Recommendation, AI Prediction, AI intelligent search, Decision Support, AI Workflow Intelligence are all part of our custom AI development services. Expertly, we incorporate AI models, application engineering, data pipelines, APIs, and user interfaces to develop scalable solutions.
Generative AI Development
The generative AI development options we offer involve integration with LLM, Retrieval-Augmented Generation (RAG), Prompt Engineering, Embeddings, Vector Search, AI Assistant, Document Intelligence, and conversational applications. We create solutions that integrate models with trusted business data and processes and consideration, response quality, access control, data protection, evaluation, scalability, and operational requirements.
AI Agents & Automation
Create intelligent agents that act intelligently, understand context, interact with systems and follow multi-step workflows. Our AI automation products integrate LLM capabilities, agent orchestration, APIs, business rules, enterprise data and workflow automation to facilitate various use cases including research, IT operations, internal support, document processing and customer service. We create suitable permissions, guardrails, and human control and escalation paths for robust enterprise adoption.
Machine Learning Development
Build machine learning solutions that convert business data to predictions, classifications, recommendations, and business action and insights. Our machine learning development services include data preparation, feature engineering, model selection, training, evaluation, deployment, and monitoring. We implement supervised and unsupervised learning methods, depending on the nature of the business problem, performance expectations, and operational environment, building models for integration into real-world applications and workflows.
Natural Language Processing
We have NLP development capabilities, supported by text classification, entity recognition, sentiment analysis, semantic search, document understanding, summarization, question answering and conversational interfaces. Using NLP along with machine learning, LLMs, embeddings, and retrieval systems, we can identify structured insights within unstructured data and develop more intelligent interactions within enterprise applications.
Computer Vision
Our computer vision development features image classification, object detection, OCR, visual inspection, document processing, image analysis and video analytics. Computer vision models can be deployed across enterprise applications, cloud platforms, and workflows to enable various applications, including quality inspection, automated document processing, anomaly detection, and asset monitoring.
AI Integration & API Development
Our AI integration services include model and LLM API integration, custom AI APIs, microservices, database integration, enterprise application integration, and workflow orchestration. We build integration layers to securely access the relevant information and trigger relevant business processes via AI services while also ensuring scalability, observability, authentication and compatibility with the current architecture.
AI Model Development & Fine-Tuning
We offer model evaluation, benchmarking, prompt optimisation, embeddings, retrieval pipelines, fine tuning, inference optimisation and model performance evaluation. Based on your data, domain requirements, privacy considerations, performance goals, and operating costs, we perform a fine-tuning assessment to determine the technical approach that is appropriate; and we help you develop models that meet specific application requirements.
Why Choose Sphinx for AI Development?
We approach AI development from both a business and engineering perspective. Before selecting models or technologies, we understand the business problem, desired outcomes, users, data, and existing technology landscape.
End-to-End AI Development Expertise
Whether it’s AI consulting and strategy, solution architecture, development, integration, deployment, or optimization, Sphinx is there to support your AI journey. This whole-of-enterprise perspective ensures the strategy and execution stay aligned and allows you to access expertise in AI when your organization requires it.
Enterprise-Ready AI Engineering
We design AI solutions to work within real enterprise technology environments. We consider APIs, applications, database platforms, cloud infrastructure, identity and access management, security needs, monitoring tools and integration architecture. This allows AI to integrate into your current business environment, instead of existing as standalone projects or tools
Practical Generative AI Development
Our emphasis is on developing meaningful generative AI applications for actual business workflows. We specialize in building LLM integrations, RAG, vector search, AI assistants, prompt engineering, and AI agents with a focus on retrieval quality, access controls, response analysis, and operational needs. The idea is to develop AI experiences that help tasks and activities more meaningful than just adding a chatbot interface.
Scalable & Maintainable Architecture
The applications designed for AI need to be adaptable. Applications that use AI should be flexible. Solutions are designed to be scalable, modular, observable, maintainable and integrative. The architecture either allows for future enhancements of an AI-powered feature or enterprise AI platform without the need to rebuild the whole solution, or both.
Responsible & Secure AI Approach
Data protection and security, access control, model behavior, human oversight, and governance are all factors that are critical when implementing AI. We ensure controls are built into the solution that are dependent on the solution’s architecture, use case, data sensitivity and regulatory environment. This doubles the transparency and visibility of data and AI capabilities that organizations can have when using AI.
Our AI Development Process
We use a holistic AI development methodology that integrates business strategy, technical skills, and iterative improvements to ensure the successful implementation of AI solutions that are both scalable and valuable for business.
1
Discovery & Requirement Analysis
This starts with understanding your business goals, issues, users, current technology environment, and data. Our team can identify the relevant points of AI opportunity, assess feasibility and outline clear requirements and measurable outcomes for the solution.
2
AI Strategy & Solution Architecture
We convert business needs to a practical AI strategy and tech roadmap. This involves choosing the appropriate AI methods, models, and technologies, designing the data infrastructure, integrating with existing systems, addressing security concerns, and determining the deployment strategy.
3
AI Solution Design & Development
The AI solution is created using AI models, data, software applications, APIs and intelligent workflows by our AI engineers. We develop capabilities around your business needs from generative AI, machine learning, AI agents and NLP, computer vision and custom AI applications.
4
Testing & AI Model Validation
The AI solution is rigorously tested to provide accurate and pertinent results. In addition to traditional software testing, we test solutions for model performance, response quality, accuracy, security, integrations, edge cases and real-world scenarios before bringing them to production.
5
Deployment & System Integration
After validation, we roll out the AI solution to the appropriate environment and connect it to your applications, data sources, APIs, and workflows. We're focused on making this secure, scalable, and production ready and fit-for-use within the bounds of your technology environment.
6
Monitoring & Continuous Optimization
As business needs, data, models, and user behaviors evolve, AI solutions must be continually assessed. Continuous monitoring of solution performance, usage, quality, reliability, and operational efficiency, with continuous improvement to ensure effective and scalable AI solutions for you.
Frequently Asked Questions (FAQs)
What are AI development services?
AI development services encompass the design, development, integration, deployment, and maintenance of AI solutions to address business or product needs. These can range from AI consulting and machine learning to generative AI, AI agents, NLP, computer vision, model development to AI integration.
How can an AI development company help my business?
An AI development company can assist in identifying valuable AI use cases, evaluating data and technical readiness, designing the right architecture, creating custom AI applications, integrating AI with existing systems, and deploying solutions into production.
What is custom AI development?
Custom AI Development involves developing an AI solution specifically for an organization’s business needs, data, workflows, applications and users. It can provide more flexibility and control than using a generic AI product.
How much does AI development cost?
The cost of the development of an AI will depend on the use case, the amount of data required, the way data is modeled, integrations, security considerations, user volume, infrastructure, and other ongoing operational needs. A focused proof of concept (POC) is likely to be a less expensive investment than a production enterprise AI platform.
How long does it take to develop an AI solution?
The timeline varies with the size and complexity of the solution. A focused proof of concept might be built quicker than a production-grade AI application that must be integrated with enterprise applications, create a custom model, implement security protocols, undergo testing, and be deployed on a specific platform. Based on the use case and its evaluation, Sphinx can develop a suitable delivery roadmap.
Can Sphinx integrate AI with our existing applications?
Yes. APIs, microservices, databases, enterprise platforms, workflows, and more can all be used to integrate AI with existing applications. The architecture is subject to your current technology environment and the type of AI you wish to deploy.
What is the difference between generative AI and traditional AI development?
Traditional AI often focuses on tasks such as prediction, classification, recommendation, anomaly detection, or pattern recognition. Generative AI focuses on producing new content such as text, code, summaries, or other outputs. Modern solutions can combine both approaches depending on the business problem.
Can you develop AI agents for business automation?
Yes. AI agents can be programmed to carry out multi-step actions, communicate with applications and information sources and facilitate business processes. The right permissions, workflow limits, monitoring, evaluation, and oversight (where needed) is also crucial in developing effective agents.
Do we need our own AI model to build an AI application?
Not necessarily. There are many foundation models, APIs, retrieval systems, or machine learning services that can be leveraged to build many AI applications. If the business has performance, domain, data, privacy or control needs, custom model development or fine-tuning may be appropriate.
How do you ensure AI solutions are secure and reliable?
The security and reliability of AI systems are not guaranteed in general but depend on the context of their architecture and application. Identity and access management, data protection, secure APIs, model testing, application testing, output assessment, monitoring and logging, human oversight, and suitable governance structures are all relevant controls.