AI Software Development Services To Grow Your Business
- Leanware Editorial Team
- 20 hours ago
- 9 min read
If you’re looking for custom AI solutions that will grow your business by tackling critical problem areas, you’ve come to the right place. Recent statistics show that AI adoption can boost revenue by up to 10%, with a fifth of industries using artificial intelligence to manage finance and services-related operations.
From machine learning models to natural language processing tools, there are a lot of options to choose from. However, a brief overview of the various types of AI technologies will help you easily identify which one is the best fit for your company.
What Are Artificial Intelligence Software Development Services?
Leanware’s AI software development services are designed to help businesses solve problems. Our services are personalized and focused on problem-solving. They range from custom AI software development and proof-of-concept services to automation solutions that cater to the specific needs of various industries.
For example, healthcare providers may use artificial intelligence to improve diagnostic precision, while retailers may use ML solutions for inventory and supply chain management.
Our team is trained to help our clients chart the best way forward and come up with a game plan that uses AI software to solve their problems.
Understanding AI Integration in Custom Software
Custom software solutions offer the greatest benefit for companies that want specialized solutions. Since these systems are built from scratch, they cater to the team’s current concerns and challenges while preparing them for future growth.
When it comes to AI integration, there are two options: developing a new and unique AI model or leveraging existing open-source APIs.
New Model: Developing an artificial intelligence for a specific company involves extensive ideation using their proprietary data. The model is trained on specific use cases that apply to the business using user experiences, customer feedback, and data-based predictive analytics.
Existing APIs: A faster approach involves using existing open-source APIs like those from Google Cloud or OpenAI to train your software on specific skills, such as image recognition or trend analysis. This is a common approach, especially preferred by small businesses, because it's more cost-effective and saves time.
When developing custom AI software, the team at Leanware follows a balanced, hybrid approach that balances speed, cost, and customization benefits.
Benefits of AI in Software Development
AI Automation: Artificial intelligence helps automate repetitive tasks like data entry or compliance checks, so your team can focus on more critical areas.
This helps drive businesses forward since their human capital is redirected towards growth-based initiatives instead of maintenance.
Data-Driven Insights: AI models sort through large data sets to identify market trends or patterns in customer behavior.
These insights allow businesses to make informed decisions based on real-world metrics instead of hypothetical projections.
Customer-Focused Services: Using AI chatbots and virtual assistants is a great way for companies to provide personalized 24/7 customer support through a reliable system.
AI software can use data analytics to provide e-commerce customers with product recommendations or patients with custom treatment plans.
Easy Scalability: The two biggest hurdles preventing scalability are the time it takes to upgrade company processes and the slow growth of teams as they onboard new members.
With intelligent AI software, businesses can use predictive analytics to allocate resources effectively and maintain lean teams even as they grow.
Our AI Development Service Offerings
Custom AI Product Development
Leanware offers custom AI product development, ranging from data-based NLP services like sentiment analysis to ML solutions like image recognition. Our developers work closely with clients from concept to deployment, designing personalized AI models that serve specific business needs.
AI-Powered Enterprise Software Solutions
Integrating AI features into enterprise applications can show extensive, immediate results.
Whether you’re setting up an intelligent supply chain or a company-wide mega data-analysis platform, these artificial intelligence software development services reduce risk and improve critical decision-making.
Using various AI models allows Leanware to fast-track the development of enterprise AI solutions. While models like GPT-4 and LLaMA have a diverse skill set, tools like the AI visual assistant Claude and chatbot Bard have more specific use cases.
Additionally, our team can also build on deep learning APIs, like Stable Diffusion, which uses text prompts to generate high-quality images, and Whisper, which can analyze or translate audio data.
Proof of Concept (PoC) & MVP Development
If you’re not ready to roll out a full-scale AI solution, you might want to explore Leanware’s MVP App Development Services. The Proof of Concept stage allows business leaders to ideate and explore feasible AI solutions, while the MVP converts approved concepts into functional prototypes for beta testing.
For high-stakes projects that don’t have clear solutions, an MVP approach reduces risks and guarantees that any AI investments deliver impactful results.
AI Consulting & Advisory Services
If you’re not sure where to start, AI consulting services will help you identify growth opportunities and develop workable strategies. Consultants will assess your current operations and provide a roadmap for potential AI implementation.
Often, these game plans will be broken up into phases based on the client’s budget and growth targets.
AI Model Training, Deployment & Support
For AI models to be effective, they need to be trained using relevant datasets. This process involves extensive A/B testing using case studies and scenarios that are relevant to a company’s industry. Even after deployment, our dev team will monitor the app to get rid of any bugs.
Leanware’s team prioritizes long-term relationships with our clients, and we provide constant support, including updates and troubleshooting after the software is launched.
Core AI Technologies We Work With
Machine Learning & Deep Learning
Machine learning technologies are designed to create algorithms that analyze data. These statistical models sort through large data sets and identify patterns independently.
You can use them to build recommendation systems, detect discrepancies in financial statements, and prevent fraud.
While ML uses simple algorithms like linear regression or decision trees, deep learning applications rely on neural network simulations. So while machine learning models are great for mid-sized datasets, they require some input from data scientists.
On the other hand, data learning systems can handle larger, more complex information and do not require any oversight. Businesses should consider the hardware requirements for both before making their choice.
Natural Language Processing (NLP)
While often linked to machine learning models, NLP allows machines to understand human language inputs, including audio and text cues. They’re often used to design chatbots, language translation tools, and voice recognition systems.
For more complex applications, like sentiment analysis, developers must coordinate between natural language processing and MLP algorithms to create suitable solutions.
Computer Vision & OCR
Different technologies are required to deal with various types of data inputs. While NLP works for human inputs, computer vision extracts information from images and videos.
Optical character recognition - a subset of CV - pulls text from these visual mediums. These algorithms facilitate applications like medical imaging analysis and automated document processing.
Predictive Analytics & Business Intelligence
AI technologies fall into two distinct categories: data extraction and data analysis. Predictive analytics uses modeling techniques to identify trends and predict future outcomes.
It applies to cases like risk assessment and customer behavior anticipation, allowing businesses to make data-driven decisions that are most likely to generate growth.
Generative AI Integration
Models like GPT-4 and DALL-E use generative AI to create text and images. You can use these to create product mockups or craft human-like content. The biggest benefit of generative AI integration is how it speeds up prototyping and ideation.
While we offer a range of artificial intelligence software development services, the developers at Leanware will identify which technologies are best for your project during the initial consultation process.
Our AI Software Development Process
Leanware’s team follows an iterative, agile process that prioritizes communication and product quality. Our developers' mindset of self-testing code allows them to find innovative solutions to problems.
Discovery & Strategy
This initial stage involves extensive communication with the clients to understand the project objectives and desired outcomes.
Our developers go the extra mile to understand the company’s core concerns and develop a strategy roadmap for AI integration that aligns with the client’s goals.
Data Preparation & Model Selection
For AI software to fully rise to the challenge, it needs the right tools and information. The data preparation phase involves gathering requirements from all stakeholders and cleaning and organizing all data so it is in a usable format.
Once the dev team has understood the nature of the problem and analyzed the available data, they can select the right AI technologies for the project.
Model Training & Validation
Our dev team will train your model using the prepared data while running iterative tests to make the results more precise. Running validation tests helps test the model against performance metrics. This phase involves several sprints to improve various aspects of the model.
Deployment & Integration
Clients are encouraged to provide live feedback while the model is under development, and improvements are made throughout the training process.
Once the AI software has been designed and trained to do a specific task, it is first deployed and then integrated into the company’s existing workflows.
Monitoring, Maintenance & Scaling
Leanware’s team continues to monitor the model post-deployment, offering support for maintenance and routine upgrades. As businesses grow, our team helps scale up software to meet their increasing needs.
AI Development Tech Stack
Programming Languages & Frameworks
Our developers are trained in a variety of programming languages and frameworks. We pick the best team for your project based on your expertise and the needs of your project.
Python is the most popular choice for AI development and entebecause of its flexibility and extensive libraries. Similarly, JavaScript is often used to design lightweight AI solutions and mobile applications.
Leanware’s frontend tech stack also includes React, Vue.js, HTML, and Angular. Backend frameworks like Django, NodeJS, and Flask support AI integration and API development.
Deep Learning Libraries & MLOps Tools
Leanware’s experts have access to extensive deep learning libraries, including TensorFlow, Pytorch, LangChain, and Metaflow, to name a few, that help them build a foundation for AI software and test prototypes faster.
Each serves different needs, so while one might work well for machine learning models, another will be ideal for LLM development.
Cloud Platforms & Big Data Technologies
Cloud platforms can offer easy access to tools and resources. For example, Google Cloud AI offers TensorFlow integration, while Microsoft Azure AI has built-in features to support custom AI software development.
Leanware’s team also relies on big data tools like Spark and Kafka to process large datasets before using them to train AI models.
Why Choose Us as Your AI Software Development Company?
Industry Experience Across Domains
Having worked in the software development sphere for over five years, Leanware’s team has a track record of success. Our AI models have solved problems and streamlined workflows for business leaders across diverse industries, including healthcare, e-commerce, fintech, education, and media.
Proven Track Record of Success Working with US Clients
Client testimonials from companies like Groundlight and Elephant speak to the success of our projects, from the quality of our software solutions to the dedication of our team. US businesses benefit from nearshoring pros, with a lack of time difference and easy communication.
“One of Leanware’s best abilities is that if there's ever a firestorm, they're always quick to put it out, so the measurability from a comfort standpoint is pretty high.”
Productivity Gains Leveraging AI
Our methodology for using AI yields a 30 percent increase in productivity. That means we can deliver results faster without compromising on quality.
Leanware’s team uses AI to automate routine tasks like data entry and document processing. However, our expert team of developers handles all high-value tasks, such as client communication and code testing.
Agile Development & Transparent Communication
Our team prioritizes effective project management. We follow an agile format with regular milestones to help us stay in touch with clients.
From Zoom or Teams calls to Slack and Jira, we adapt to client workflows seamlessly.
We believe in providing a well-rounded service, and Leanware’s teams often consist of software developers, project managers, and product designers, with CEO Carlos Martinez at the helm. This hands-on approach to client engagement helps us develop finely tuned solutions that guarantee results.
FAQs on AI Software Development
What does an AI software developer do?
An AI software developer oversees various frontend and backend tasks. During the various project phases, they collect and clean the data, select an appropriate tech stack, train the AI model according to client requirements, and run various stages of tests to fine-tune the application before deployment.