AI Software Development

Unlocking actionable insights and opportunities personalized for every business

When to use AI

Factors to determine if AI is a good fit for your business

Artificial Intelligence can be the right fit for your business, if your organization has:

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AI Applications in Business

AI software development across core business functions

  • Document assembly (automation) tools for the drafting of legal documents through forms and databases using “if-then” decision-tree logic
  • Document mining and benchmarking tools to identify and compare legal documents, policies, and contractual provisions
  • Document revision and analysis tools to analyze drafted language with transactional considerations in mind in order to evaluate the textual use and effectiveness
  • Analysis of historical and existing data patterns to make predictions and improve the performance of supply chain, set prices that maximize profits, and launch products/ services that exactly meet customer needs
  • Business leaders can understand what causes customer churn and how they can prevent it by innovating continuously
  • Explains how the business is impacted by the volatility and unpredictability of commodity prices through near-real pricing forecasts
  • Better understanding of historical data and hidden patterns improve the ability of business to forecast market growth
  • ML algorithms leverage big data to deliver personalized recommendations that suit each customer’s tastes and preferences across all touchpoints
  • AI recommender systems enable customers to discover products and services they might otherwise have not found on their own
  • Recommendations AI equips companies to influence and shape customer decisions, improve customer retention, increase sales, and boost cart value
  • Context-aware bots with the ability to self-learn continuously from prior interactions and improve their responses over time
  • Predictive intelligence and analytics to personalize interactions based on a customer’s profile, preferences, and past behavior
  • Integrates easily with any legacy/ back-end systems and specializes in completing conversations (tasks) by interacting with multiple systems
  • Personalized course recommendations based on user behavior
  • Tailoring of eLearning content to each learner based on their learning needs
  • Targeted allocation of resources and learning content to save time
  • Real-time learning assistance provided through AI-driven chatbots
  • Automated knowledge checks
  • AI helps analyze numerical and natural language data, referencing relevant insurance policy information, healthcare forms, and other input documents
  • Analyzes claims management data to provide insightful recommendations to knowledge workers, so they can determine eligible claims, and percentage of payout
  • ML algorithms can be trained to quickly spot “red flags” in fraudulent claims and risk management data, giving knowledge workers more time to spend on complex cases

Success stories

Examples of AI in business

1. Custom AI software to manage employee compensation claims
Fingent developed a custom AI software to enhance and expedite the tasks involved in processing workers’ compensation claims. The software employs Optical Character Recognition (OCR) and AI for smart data extraction and leverages contextual analysis to extract meaningful insights from larger datasets.
2. AI-powered virtual assistant to manage employee Q&A
Across several organizations, HR teams are forced to spend their time on routine and mundane tasks, like answering common employee questions. To solve this dilemma and prevent productivity loss in HRM, Fingent built an AI-powered virtual assistant (chatbot) that handles the most common questions asked by employees.
3. AI-powered people development platform
Artificial intelligence offers a sound solution to personalize learning for each individual, while not compromising the learning goals. Skill Lake, a people development platform built by Fingent, leverages AI and ML to facilitate continuous and personalized learning for organizational training providers.

Our AI success stories shed light on how we help businesses attain growth by leveraging intelligent technologies and new business models.

AI Integrations For Business

AI integrations to improve the performance of existing business systems

Customer service and support : AI-powered chatbots use machine learning algorithms and natural language processing to understand customer requests and respond appropriately faster than human workers and at lower costs. Drawing on customer data and predictive analytics, AI can also power recommendation functions.
Supply chain management : Machine learning algorithms can forecast demand level variations allowing businesses to create more efficient and cost-effective supply chains. By eliminating the risks of overstocking as well as running short on in-demand products, supply chain leaders will better know the optimal time to move supplies.
Intelligent decision making : Even in times of great uncertainty, AI- and ML-based algorithms allow business leaders to navigate change and elevate decision making across operational and customer-facing processes. The combination of data analytics and machine learning improve both customer and operations intelligence, so businesses can seamlessly shift from being reactive to proactive.
Enterprise IT automation : Using AI to predict, automate, and optimize many of the data center tasks that humans currently perform will significantly reduce the amount of human error in operational activities. AI-defined infrastructure and automated IT systems enable optimum cost utilization for infrastructure, enhance the security of data center operations, and improve the quality of services provided to customers.
Sales and marketing : Modern sales and marketing teams have access to more data than ever before. AI can assist marketers to deeply understand their customers’ behavior, actions, and indications, so they can target the right strategy to the right person in a time-saving and effective way. AI allows sales teams to improve sales forecasting, pipeline analysis, and buying group visibility, so they get more opportunities to drive greater sales ROI.

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Infrastructure requirements

Infrastructure considerations and criteria for AI software development

Infrastructure requirements for implementing AI in business:

Securing AI solution

Security measures to protect AI systems and applications in business

Pros & Cons of AI

Benefits and risks of implementing AI in business


AI Tools & Technologies

AI technologies and tools to reimagine business operations

Top technologies that drive AI in business
Artificial Intelligence is not just one technology, it’s a select assortment of multiple cognitive technologies:
Custom AI software development is the best tool to accelerate business growth and profitability
Custom artificial intelligence software development services:

Custom-made AI software offers just what you need - nothing more, nothing less.

Support & Maintenance

Managing custom AI software support and maintenance

Managing the maintenance of AI software:
Artificial Intelligence is not just one technology, it’s a select assortment of multiple cognitive technologies:
Managing support for AI software:

Cost of AI implementation

Estimating the time, resources, and budget for AI implementation

Factors that influence AI software development cost:

Planning your AI investments with a trusted outsourcing partner will fetch you benefits that outweigh expenses.

Success & ROI

Measuring the success and ROI of AI software development

Planning the ROI from AI might be challenging, but following a few rules can help turn AI into a profitable investment for executives.
Assess holistically : While assessing and predicting AI’ ROI, consider the uncertainties of AI models, such as their exact error rate, changes in model performance, maintenance requirements over time, and how different AI initiatives could impact each other’s results.
Create a portfolio : Just like how you assess and predict the ROI of product innovations or financial investments in other areas of business, create and assess a mix of initiatives that will increase the chance of delivering the expected results. For instance, adopting a portfolio approach by applying test-and-learn, risk-return, and competitiveness-investment trade off could demonstrate how AI will pay off your business.
Integrated lifecycle management: Instead of managing individual AI projects, managing an integrated data-AI-cloud lifecycle will finetune project execution and avoid downside ROI surprises.
Investments and returns in AI software development

AI Investments

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