SPD Technology is an AI/ML development company and Select-tier member of Anthropic’s Claude Partner Network. Our AI and ML development services cover custom machine learning models, generative and agentic AI applications, computer vision systems and intelligent automation for enterprise and high-growth technology companies across fintech, eCommerce, healthcare and manufacturing.
Across recent projects, that expertise translated into tracked results:
Our AI/ML expertise spans startups and enterprises alike, whatever your industry, scale, or technical starting point, we have the depth to deliver.
From production-grade ML models and RAG-based generative AI to computer vision systems and intelligent automation pipelines, our custom AI/ML software development services are scoped around your business problem, your data and the systems you already run.
As an AI development company, we guide AI adoption with tailored consulting at every step. Our engineers can develop a solid strategy to build a new AI-based system or navigate all the complexities of transition from old systems to AI-powered ones. This includes AI readiness assessments, build vs. integrate decision frameworks, and compliance scoping for regulated industries — the same approach we used when developing AI strategies for clients across fintech, manufacturing, retail, and other industries.
We create computer vision solutions that enable image and video analysis, object detection, object recognition, and task automation. Our team knows how to enhance quality control in manufacturing, enable facial recognition in security systems, and improve customer experience across the industries. With the latter goal in mind, we created instance segmentation and deep imbalance regression models for CV-enabled API, promoting automation and introducing paid features in a veterinary care app for boosted revenues.
We use generative AI for automated product descriptions, categorization, personalized marketing messages. Our team has delivered ChatGPT functionality into an eCommerce project to categorize over a million items and create marketing descriptions. We build RAG-based enterprise assistants that answer questions from proprietary knowledge bases and fine-tune foundation models for domain-specific tasks. For VayaPin, we built LLM place classification and 7-language content generation, with all production code written in Claude Code.
Blending machine learning expertise and intelligent automation technologies, we empower organizations to streamline processes and enhance business efficiency. From process discovery and analysis to AI-driven cognitive automation, we develop AI models to optimize workflows and improve decision-making. One such task was executed for our client within B2B intelligence services. We provided automated data collection and processing for their system using NLP and ML models, resulting in a 3x increase in document processing speed and a fivefold reduction in operational costs.
Through MLOps and model lifecycle management and AI integrations, we optimize ML solutions and set up deployment, monitoring and retraining. Our expertise is backed by integrating NLP and the YOLO model and implementing Camelot and AWS Textract. For a US payments startup, we deployed a LightGBM and sentence-transformer classifier on AWS ECS that determines FSA/HSA eligibility with 80%+ accuracy and supports release cycles of less than a day. And with the help of MLOps, we automate and streamline ML development and take care of ML model lifecycle management.
We build RPA solutions that automate rule-based business processes such as document processing, data validation, system integrations, and compliance workflows. Using UiPath, Automation Anywhere, and custom Python-based automation pipelines, we develop RPA components that seamlessly integrate with existing systems, enabling smooth data exchange and workflow orchestration. Our automation work has delivered 100% automation of back-office phone calls for one client, the same approach we apply across manufacturing, fintech, and logistics.
We are experts in utilizing Dialogflow, Microsoft Bot Framework, IBM Watson Assistant, and Rasa for delivering AI chatbots. Drawing on this experience, we developed an AI-powered chatbot for HaulHub that selects data from the database and engages clients in conversation, now being extended with RAG for deeper contextual accuracy. In a separate engagement, we deployed a high-load LangChain + LLM chatbot for a fashion retailer.
With AI and ML, we transform unstructured data into valuable insights and create solutions for sentiment analysis, entity extraction, text classification, named entity recognition, text summarization, and language translation. Integrating enterprise NLP and language model applications with custom AI solutions enables us to understand text meaning and context. We built an NLP tool that classifies invoice lines from 450 vendors into 33 classes, feeds them into the client’s CRM via API and fully automates invoice processing for a manufacturer.
Our agentic AI covers single-agent systems with tool use, multi-agent orchestration that automates complex tasks across enterprise, and ReAct and Plan-and-Execute patterns with guardrail systems for production safety. We work with LangChain Agents, AutoGen, and CrewAI. For Space Needle, our Claude Code enablement raised merged pull requests 89% at constant headcount and cut human-reported bugs 81%. Our incident pilot agent for a US cashback fintech delivers a PR-ready fix about 24 minutes after a production incident is detected.
Utilizing AI and ML for fraud detection algorithms and prevention systems, we protect organizations dealing with sensitive data from threats. Our competence is supported by the implementation of an automated fraud prevention functionality for Blackhawk Network, a financial technology company. This custom AI solution automates the registration flow with OFAC and EIN/SSN verification for drastic time and cost savings for new business onboarding.
John Gabbert
Founder and CEO, PitchBook Data
Customers are king at PitchBook and SPD Technology shares in this mission. For the last 13 years, SPD Technology has helped us scale product development and continuously deliver the product functionality our clients need to make smarter decisions.
We delivered projects across fintech, eCommerce, hospitality, healthcare, and construction, each with a specific problem, a defined approach, and a result we can put a number on.
merged engineering output and 81% fewer bugs after Claude Code engineering enablement for Space Needle
from production incident to PR-ready fix for a US cashback fintech with our agentic incident pilot
search-to-purchase conversion increase through an AWS Bedrock-powered AI search assistant for a gift card store
cost reduction in document data processing through NLP and ML automation for a B2B intelligence company
products categorized with ~90% accuracy through ChatGPT-powered categorization and AI scraping for a US online retailer
AI eligibility accuracy for FSA/HSA payments through an ML classifier built for a US payments startup
built for children’s education: lightweight, self-hostable and deployable via AWS Bedrock at lower cost
reduction in manual data processing workload for a global investment data analysis platform through AI-powered automation
To share their experiences
Sara Lufrano
Principal Technical Product Manager, Space Needle
Always delivered on time. Highly responsive to our needs. 10/10.
Alex Samano
Co-Founder & CEO, Mogami App
SPD Technology has done a great job of maintaining the lifeblood of their codes. They’re transparent with pricing models and deliver within budget. Their dedicated teams act as an extension of the partner’s company. Responsibility and a commitment long-term partnership are two hallmarks of their work.
Fabrice Forget
Chief Product Officer, PitchBook
We feel very lucky to have found SPD Technology as our partner. Over the last 10 years, they have totally surpassed our expectations, and day after day we have received incredible value from the team. Here is the secret sauce, just put together your best ideas in your requirements and there is nothing they can’t do!
Shariq Ahmad
Head of Technology, Morningstar, Inc
All of their developers and technology staff are highly talented and very professional. Working with SPD felt like we were working with an internal team. They are always accessible any time of the day and very flexible in providing support to our users who are globally distributed.
Prasad Sridhar
Senior Engineering Manager eCommerce Solutions Company
SPD Technology’s work has been praised by the client for their consistency and high quality. Their communicative, responsive, and flexible project management ensures a positive collaboration. Ultimately, their professionalism and forward-thinking are impressive.
Steve Carner
Founder CEO, Home Hub
The team at SPD Technology exceeds expectations. Their professional communication style makes them stand out, They’re a skilled group of detailed-oriented workers. Customers can expect a team that provides helpful suggestions to better their clients.
Our AI/ML engineering covers every layer of delivery: data pipeline design, model training, MLOps infrastructure, explainable AI frameworks, and HIPAA/GDPR-compliant production deployment.
Our team ensures seamless data management by using services like AWS S3 for data storage and AWS Glue for ETL processes. Our data warehousing services give models clean, well-structured data sets for training and inference at scale.
We design task-specific ML models tailored to specific requirements of complex AI solutions. Our team utilizes advanced algorithms and deep learning techniques from libraries like TensorFlow or Hugging Face to solve nuanced tasks such as image captioning and text cleanup.
Leveraging LIME for explainable AI and IBM’s AI Fairness 360 for bias detection, our AI development services prioritize transparency and fairness in our models. Our team ensures insights into model decisions for you to harness AI capabilities.
Our expertise in FairML and IBM Watson’s AI OpenScale help us maintain ethical standards and fairness in ML solutions. We’ve delivered projects for fintech, banking, healthcare, and legaltech, where we prioritized the responsible usage of AI technologies.
Our AI development company delivers highly scalable eCommerce platforms that handle web scraping thousands of products at a high speed. We also design robust architectures with AWS Sagemaker for scalable model deployment and AWS Lambda for serverless computing.
We build CV and AI systems for healthcare and financial apps to HIPAA, GDPR and OFAC requirements. Plus, we use AWS Key Management Service and AWS SageMaker for data encryption and secure model deployment.
Our AI developers manage the deployment process with our competence in TensorFlow, Amazon SageMaker, Google AI Platform and Azure Machine Learning. During the deployment process, we prioritize AI model scalability, latency and seamless integration into existing workflows.
By prioritizing user experience and accessibility, our AI app development services create immersive human-AI interactions with the help of Hugging Face’s Transformers for NLP interfaces and AWS Transcribe for voice recognition systems. For AI agents that write code, we add human approval gates and audit trails.
Our AI and machine learning development services incorporate specific domain knowledge, drawing on our extensive experience in projects for diverse industries.
We help fintech companies build secure, efficient systems for payment processing and facilitation, drawing on over a decade of fintech delivery. For Blackhawk Network, we automated the business registration flow with OFAC and EIN/SSN verification, and for a US cashback fintech our incident pilot agent prepares a PR-ready fix about 24 minutes after a production incident is detected. Our artificial intelligence and machine learning development for fintech also covers FSA/HSA eligibility classification, AML systems, predictive analytics and credit card fraud detection using machine learning, built into the payment software our clients already run.
Our AI software development drives growth and customer engagement for eCommerce businesses and retail companies by deploying scalable and high-performance systems. Our expertise centers on clean product catalog data, relevant search and recommendations, and AI support tools that stay fast during seasonal traffic peaks. For a US online retailer, we used ChatGPT API and image recognition to categorize products, refine catalog data and improve search. We also build personalized marketing campaigns, demand forecasting and product range expansion for online retailers.
We build artificial intelligence solutions for hospitality and tourism companies that run high-traffic booking, ticketing and guest-facing systems. Our focus is on making these platforms faster to change and more reliable to operate. For the Space Needle ticketing platform, we introduced AI-native engineering with Claude Code and automated incident triage, with engineers approving every code change and release. The same setup suits booking, ticketing and guest-service platforms that need frequent, reliable releases.
With experience in ML services for the construction sector and logistics and supply chain, we improve project planning, risk management, safety compliance, route optimization and demand forecasting. For HaulHub, we combined OpenAI ChatGPT and AWS Bedrock models (Claude, Titan and Jurassic) for image processing, data classification and a chatbot that lets clients query the data layer, and built the SupplierCI system that manages and analyzes over 70 million records for construction supply chain analytics.
Our healthcare software and AI-powered solutions aim to enhance patient care, optimize clinical workflows, and improve healthcare outcomes. We delivered a HIPAA-adjacent computer vision iOS app achieving 95%+ AI/ML model accuracy and 90% accuracy in detecting facial imperfections built on a custom medically-expert-labeled dataset developed in collaboration with a specialist physician. We have extensive experience developing HIPAA-compliant software, and for a UK life sciences SaaS company we built GxP-traceable supply chain data integration (AS2, SFTP, EDI and XML under 21 CFR Part 11, Annex 11 and GAMP 5) that serves as a validated data foundation for AI.
Our expertise for the manufacturing industry covers the data manufacturing AI depends on: unstructured documents such as supplier invoices and repair records, equipment data, and the ERP and CRM systems that models have to integrate with. For a liquid packaging manufacturer, our ML solution sorted invoice data across more than 30 classes and fed it into the client’s CRM, creating a fully automated document processing pipeline. On the equipment side, our predictive maintenance algorithms help companies identify potential equipment failures before they occur.
Our machine learning services support legal teams and legaltech platforms with document intelligence, scheduling automation, and compliance-aware workflows, where our team prioritizes auditability and explainability. In practice, we delivered a legal scheduling platform that automated email generation, document drafting, and court availability parsing, reducing scheduling time from 35 minutes to under 1 minute with no human intervention.
Our artificial intelligence projects for insurance companies start with the data layer that underwriting, pricing and claims models depend on. For Pie Insurance, a US workers’ compensation insurer, we built an Operational Data Maintenance platform with ETL pipelines that consolidate, clean and automatically refresh state-specific rate data from spreadsheets and CSV files, alongside a new billing system. Together, the work tripled ACH payment adoption, saved the customer success team 40% of operational time and raised the average check by 30%.
From Fintech industry stalwarts to industry-leading eCommerce providers, we ensure the comprehensive alignment between emerging technologies and established business processes.
Every AI project has a different definition of done. Our delivery process for AI/ML development services starts by establishing yours. Then builds toward it through five structured stages, with measurable checkpoints at each step.
Before recommending anything, we assess your data availability and quality, existing infrastructure, compliance requirements (GDPR, HIPAA, SOC 2), and a clear definition of the business problem. As a result, we get a written architecture recommendation with build vs. integrate decision rationale and a data readiness scorecard.
We design the full system before a single line of model code is written, including model architecture selection (classification, detection, generative, or agentic), data pipeline design, MLOps infrastructure plan, and compliance architecture. Success metrics and evaluation benchmarks are locked in at this stage.
We build, train, and validate custom models against predefined benchmarks, applying fine-tuning, RLHF, or domain adaptation. Proof-of-concept and validation work also depends on data preparation, including structuring, cleaning, and validating data before training and testing. Evaluation is framework-specific: ROUGE and BERTScore for language tasks, mAP for detection, F1 and AUC-ROC for classification. Models are confirmed production-ready before integration begins.
We establish CI/CD pipelines for ML, configure drift detection and performance monitoring dashboards, and set up human-in-the-loop reviews where required. Deployment targets, such as AWS SageMaker, Google AI Platform, or Azure ML, are selected based on your existing infrastructure.
Production data shifts. Models that perform well at launch degrade without active management. We set retraining trigger thresholds from day one, monitor output quality continuously, and structure ongoing maintenance as a defined engagement.
A smooth AI/ML engagement depends on how expectations are set, how IP is protected, how costs are scoped, and how problems are handled when they surface.
We clearly define ownership and rights in contracts for code and ideas in artificial intelligence projects. You can rely on us as we employ NDAs along with other legal measures to safeguard client intellectual property throughout the development process.
Careful planning, clear deliverables, transparent communication across time zones, and regular reporting are the irreplaceable parts of our project management. Together we will establish convenient communication channels to ensure the project is on the right track.
When AI agents write or review code, we define which actions need human approval, keep audit trails of agent activity, and set guardrails before anything reaches production, as in our Claude Code engineering engagements.
Through our close collaboration with you during project discovery, we will elaborate on an accurate estimate, specifying the resources needed. Based on the projected scope of work and risks, we ensure that you have a clear understanding of the cost structure on each of the project’s milestones.
With 20 years of experience in the market and a convincing portfolio that includes partnerships with prominent clients, we have established ourselves as a reliable AI/ML development services company. Our track record of client success reassures our clients of our ability to meet their business needs.
We combine AI/ML expertise with industry knowledge and each client’s business context to deliver products across different sectors. Plus, through rigorous recruitment and retention practices, we ensure our team members are highly qualified and committed to continuous expertise growth.
Different projects need different structures for AI and ML development services. Whether you need one specialist embedded in your team or a fully autonomous delivery unit, we scope the engagement to fit your project.
This model allows you to quickly enhance your in-house team for artificial intelligence services by adding one or more AI experts. It’s ideal for filling expertise gaps or scaling up your team temporarily. With team extension, you can seamlessly integrate additional talent into your existing workforce, facilitating smooth collaboration and efficient project execution.
For over 20 years, SPD Technology has built custom software for fintech, eCommerce, healthcare and other industries, and it is now a Select-tier member of Anthropic’s Claude Partner Network. As an experienced AI development company, we quickly embraced artificial intelligence and machine learning technologies to accelerate digital transformation, improve operational efficiency, facilitate data collection, enhance customer engagement, improve decision-making, help organizations scale AI initiatives, and more. Because our engineers and data scientists hold PhDs and possess deep expertise in AI/ML development, deep learning, natural language processing (NLP), and computer vision, we rapidly adopted the full potential of modern AI technologies.
Our team has repeatedly demonstrated the ability to leverage AI to solve complex operational challenges and drive successful AI adoption across industries. We have delivered AI solutions ranging from fraud detection powered by advanced anomaly-detection models in fintech to AI-driven chatbots that enhance customer service through generative AI and NLP in retail. In healthcare and veterinary care, we applied image recognition and computer vision to improve diagnostic precision.
With extensive experience in AI consulting and hands-on AI development, our team takes AI-powered solutions from proof of concept to production for clients across industries.
By Independent Organizations
Helping global businesses implement Adyen payment solutions with secure architecture and optimized transaction flows.
Confirmed by Oracle certification, our company provides top-notch tech expertise in building and delivering cutting-edge database and cloud-based apps.
IIBA Certification signifies our proficiency in business analysis, ensuring a deep understanding of client needs and industry requirements.rn
With AWS Certification, we guarantee top-tier cloud expertise, enabling us to architect robust, scalable, and secure solutions.
Trusting your project development to us, you can rely on our project management excellence, meticulous planning, and efficient resource utilization. rn
Our Scrum Alliance Certification demonstrates our dedication to agile methodologies, fostering collaboration and iterative development.rn
Backed by Scrum.org Certification, our development team leverages the best principles of Scrum to build superior and iterative software solutions.
Answering the most frequently asked questions about AI software development services.
AI/ML services are the consulting, data, model development, integration and MLOps work needed to put artificial intelligence and machine learning into production. They range from building custom models and generative or agentic AI applications to deploying, monitoring and retraining them inside existing systems. Companies usually bring in an AI/ML development services provider when a use case needs custom models, proprietary data or integration with systems they already run.
Artificial intelligence and machine learning development services become essential when your business processes require measurable improvements, such as reduced costs, faster processing, or improved accuracy, and traditional tools can’t scale with growing data or complexity. At this stage, investing in AI adoption with custom AI development allows you to build tailored AI models and more complex AI solutions that align with your specific workflows and unlock new levels of automation.
AI services use custom AI models to uncover hidden patterns in large datasets, deliver data-driven insights, and automate routine tasks. This boosts productivity, eliminates inefficiencies, and allows employees to focus on strategic work that drives business growth. For example:
To find the right AI software development company, start by clarifying your goals, data strategy, and technical requirements. From there, look for partners with proven domain experience, strong case studies, and a mature approach to AI adoption.
Providers of the best AI development services help you prioritize high-impact use cases, integrate AI seamlessly into existing systems, and define clear KPIs for success. A truly reliable partner also stays with you long after launch, providing ongoing support, monitoring performance, and retraining or fine-tuning your AI models as your data and business goals evolve. When you compare vendors, ask for production metrics from past projects and how humans review and approve actions taken by AI.
An AI readiness assessment evaluates your data, processes, infrastructure, and existing enterprise systems to define a clear roadmap for adoption. Delivered as part of AI consulting, it pinpoints high-impact use cases, guides custom AI development and custom AI models, and enforces strong governance with robust data management practices for integration.
Any AI app development company will say that the timeline depends on scope, business objectives, and data readiness. An AI proof of concept validating one use case on existing data takes 4-8 weeks.
An AI MVP with a production-ready model, integration, and monitoring takes 3-6 months.
A full end-to-end AI system with multiple models, MLOps infrastructure, compliance controls, and enterprise integrations typically takes 6-12+ months. The single most variable factor is data readiness since projects where labeled training data does not yet exist add significant preparation time before model training begins.
We choose AI tools and ML frameworks by task, data and deployment environment:
The development costs of artificial intelligence and machine learning solutions depend on three primary factors:
A focused proof of concept validating one use case typically takes 4-8 weeks of effort. An MVP-level AI feature integrated into production takes 3-6 months. Full end-to-end AI systems with MLOps, compliance, and enterprise integrations take 6-12+ months.
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