Artificial Intelligence Consulting Services
An experienced AI consulting partner, ScienceSoft designs state-of-the-art solutions fully tailored to our clients’ unique needs and figures out the ways to speed up AI development, ensure optimal project cost, and minimized risks.
Artificial intelligence (AI) consulting is a proven way to get expert guidance on leveraging AI technologies and effective AI integration into business operations.
With 35 years of experience in artificial intelligence and 750+ IT professionals on board, ScienceSoft provides all-encompassing assistance across AI implementation to help businesses design, develop, and seamlessly maintain cutting-edge AI solutions.
What Makes ScienceSoft a Reliable AI Software Development Company
- AI consultants and developers with 7–20 years of relevant experience and competencies in major ML technologies, frameworks, and libraries.
- Deep expertise in AI-associated services: since 2005 in business intelligence and data warehousing, since 2013 in big data and image analysis.
- Domain experience in 30+ industries, including financial services, healthcare, manufacturing, retail, telecoms.
- Expertise in industry-specific standards (HIPAA, GAMP, PCI DSS, GLBA, etc.) to create compliant AI solutions.
- In-house PMO and established project management practices to handle large-scale and distributed projects and drive them to their goals despite of time and budget constraints.
- ISO 9001 and ISO 27001-certified to ensure high quality of AI services and full security of the customers’ data.
- DevSecOps approach to create a strongly protected environment for data processing and storage.
Trusted by global market leaders
What makes ScienceSoft different
We achieve project success no matter what
ScienceSoft does not pass mere project administration off as project management, a practice that's unfortunately common in the market. We drive projects to their goals, mitigating risks and overcoming constraints.
Our Clients Say
ScienceSoft was to cover end-to-end development of an intelligent paperless invoice processing module.
They selected and implemented techs that ensured the system’s availability and fault-tolerance in the future. We were particularly pleased with neat alignment of the developed module with our requirements.
We have cooperated with ScienceSoft on the evolution of our main product, an Al-powered tool that helps detect and fix vulnerabilities in software code.
ScienceSoft's team did a solid job for us. They are extremely competent and committed. Our collaboration was straightforward and efficient, and we would certainly recommend ScienceSoft as a reliable service provider.
They delivered a fully customized AI medical chatbot PoC in just two weeks, which was unbelievable.
The attention to detail in the chatbot design, and especially the pitch deck, was amazing — with this kit on hand, we are ready to go into investor discussions confidently. It’s not often that you find a team that moves this fast without sacrificing quality.
AI Software and Capabilities ScienceSoft Specializes In
With practical experience in 30+ industries, ScienceSoft is an AI consulting company that tailors AI solutions to the specific needs of each domain, including healthcare, banking, insurance, lending, investment, manufacturing, retail & ecommerce, advertising, education, professional services.
Business area perspective
Customer service and support
- Virtual customer agents (chatbots, digital humans) providing assistance on any issues.
- Speech-to-text and text-to-speech conversion.
- Customer sentiment analysis.
- AI-powered recommendations for next-best actions for human agents.
Value you get: enhanced rates of customer request resolution, reduced customer service labor costs, increased customer satisfaction and loyalty.
Financial management
- Financial performance and risk forecasting.
- Financial modeling.
- Prescriptive financial planning (budgeting, cost optimization, debt collection, risk hedging, M&O, etc.).
- Financial fraud detection.
For financial services:
- Customer risk assessment and credit scoring.
- Automated compliance checks.
- AI-supported decision-making, e.g., on bank account opening, loan origination, AI for mortgage, AI for insurance claims, AI for underwriting, and investing in a particular asset.
- Debt collection management.
- Payment processing enhancement.
Value you get: minimized financial risks, faster financial workflows, optimized costs, increase in profitability.
- Demand forecasting and demand-driven supply chain planning.
- Multi-echelon inventory optimization.
- Calculating optimal stock replenishment dates and amounts.
- Analytics-based supplier selection.
- Transportation mode and route optimization.
- Automating and optimizing warehouse and yard operations.
- Inventory counting with computer vision.
- Digital twins.
Value you get: supply-demand balance, minimized supply chain risks, reduced procurement, shipment, storage, and labor costs.
Diagnosing, treatment, and medical imaging
- Enhanced management of electronic health records (EHRs) and patient records using AI in EHR systems to ensure accurate, streamlined data handling.
- Streamlined and more accurate identification of diseases, side effects, and factors that affect health conditions due to AI-supported diagnostics and medical image analysis.
- Improved quality and safety of patient treatment thanks to intelligent prescriptions and instant risk factor identification (e.g., drug interactions, potential side effects).
- Early detection of potential health issues with AI-enabled remote patient monitoring integration with AI-powered medical devices.
- Streamlined population health analytics across large-scale, heterogeneous data sets.
- Improved patient engagement with medical AI chatbots for initial consultations and ongoing support.
Value you get: cost and time savings, high diagnostics accuracy, state-of-the-art patient care, and treatment safety.
Asset maintenance
- Predicting failure probability over time/in a certain number of steps.
- Flagging anomalous behavior of machinery and equipment.
- Forecasting remaining useful lifetime.
- Suggestions on the proper asset maintenance time.
- AI-guided maintenance operations.
Value you get: improved OEE and productivity, decreased maintenance and repair costs, increased asset lifetime and uptime.
Sales and marketing
- Customer behavioral analytics, including face and emotion recognition.
- Customer segmentation.
- Cross-selling and upselling recommendations.
- Intelligent prescriptions on optimal segment-specific sales and marketing strategies.
- Automated calculation of personalized prices, creating individual offers.
- Dynamic pricing.
Value you get: increased sales, conversion rates, and average order value.
Document management
- Extraction, validation, and analysis of data from digital documents.
- Conversion of paper documents to a user-defined digital format.
- Automated document creation.
Value you get: faster and more accurate document processing, reduced document-associated costs.
Production management
- Production scheduling and optimization.
- Product line optimization.
- Quality control and defect detection.
- Real-time performance monitoring.
- Predictive and preventive equipment maintenance.
- Energy consumption optimization.
Value you get: cost- and performance-efficient scheduling, enhanced production quality, and increased sustainability.
Bird’s-eye view
Chatbots
Industry-specific virtual assistants
Conversational AI
Text-to-speech and speech-to-text
Speech recognition
Generative AI (like ChatGPT, DALL-E, MuseNet)
Business automation
Predictive and prescriptive analytics engines
AIOps solutions
AIoT solutions
Copilots
Autonomous vehicles and ADAS
Image analysis systems
Computer vision systems
Fraud detection for digital and physical environments
Our Artificial Intelligence Portfolio
32 results for:
End-to-End AI Consulting Services by ScienceSoft
The scope of ScienceSoft’s artificial intelligence consulting services varies depending on our clients’ business needs, maturity of the data management practices, and the current AI environment. The AI development steps may include:
1
Business analysis
- For enterprises: definition and analysis of business needs to be pursued with an AI solution; analysis of the existing AI environment (if any), data management practices established within the company, the currently used technologies and tools.
- For software product companies: development of the competitive advantage framework, including TA definition, identification of features to win the competition.
2
AI solution conceptualization and development project planning
- Designing the architecture and feature set of the AI solution and creating the optimal tech stack for AI implementation.
- AI project planning: deliverables and KPIs, cost and timeline estimates, a risk management strategy, etc.
- Defining the approach to the AI models for the solution-to-be: going for proprietary models development or choosing public-available services and open-source models.
- Designing user-friendly UX and UI.
- AI solution PoC delivery (optional).
3
Data preparation management (for proprietary models)
- Exploratory analysis of the existing data sources (data type, volume, etc.).
- Data gathering and cleansing (standardizing, replacing missing and deviating variables, anonymizing sensitive data) for ML model training.
- Splitting data into sets for training, validation, and testing.
4
AI solution development
- For proprietary models: ML model refinement, testing, evaluation, and deployment.
- For open-source models: ML model/service integration; additional model’s training (if needed)
- Non-AI part development, including DevOps implementation and coding of the server side.
5
AI solution quality assurance
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Continuous testing throught development.
- End-to-end AI system testing.
- Evaluating the quality of AI solution output according to pre-defined KPIs.
6
AI solution support and optimization
- Continuous AI solution monitoring and optimization.
- Adding new data sources to feed the AI solution for greater accuracy and insight.
- Building new ML models to meet the newly arisen business needs.
AI Service Costs
Pricing models ScienceSoft uses
Time and Materials
Best for:
- Agile development of AI-based solutions.
- Continuous consulting during AI implementation.
- Iterative AI software evolution, reengineering, bug fixing.
Fixed price
Best for:
- One-time consulting activities (e.g., AI solution architecture design, code audit, project planning).
- Feasibility study and PoC development.
- Fixed-scoped tasks (e.g., building a particular AI-supported feature, AI model development, one-time AI solution testing).
Subscription fee
Best for:
- AI infrastructure management (data center management, AI software configuration, cloud resource optimization, etc.).
- Managed AI security and compliance.
- L1–L3 help desk (a per-ticket model applies as well).
Sample cost ranges of AI consulting
$15,000
AI product consulting for startups.
$6,000–$140,000
Consulting on an enterprise AI solution:
- Ideation and feasibility study: $6,000–$24,000
- Implementation: $18,000– $140,000
- Evolution: $24,000/year– $140,000/year
Sample cost ranges for AI development
$30,000–$200,000
Building an AI-based software component (forecasting, optimization, etc.).
~$120,000–$300,000
Developing an AI-powered virtual assistant (chatbot).
~$200,000–$600,000
Creating an AI-enabled automation solution of average complexity.
~$800,000–$1,000,000+
Implementing a large-scale analytics system powered with AI and big data.
To get a customized estimate for your solution, use our online cost calculator.
AI-Based Software Development Cost Estimation
Please answer a few simple questions about your needs to help our experts calculate the cost and timelines for your AI-based software development project quicker.
Thank you for your request!
We will analyze your case and get back to you within a business day to share a ballpark estimate.
In the meantime, would you like to learn more about ScienceSoft?
- Project success no matter what: learn how we make good on our mission.
- 4,000 successful projects: explore our portfolio.
- 1,300+ incredible clients: read what they say.
What’s best for your project: a custom AI model or a pre-trained one?
If the target solution is to perform common tasks like speech recognition or text summarization, open-source or licensed AI models (e.g., from Microsoft and Amazon) are typically the best option. When customized to suit a particular use case and additionally trained on your data, they demonstrate high accuracy and can significantly optimize development costs. For example, we used five open-source neural network (NN) models to add call transcription and sentiment analysis capabilities to our client’s help desk software product.
Custom models are worth the effort and investment when high precision and exceptional security are required. They are more common for tasks like medical diagnosis, credit risk assessment, and quality control in manufacturing. When from-scratch development is needed, there can be some other ways to optimize costs. For example, one solution is to retrain existing models or use internal and publicly available data sets.
More From Our Experts on AI in Finance and Healthcare
AI in lending
ScienceSoft relies on 35 years of experience in AI and 19 years in loan software development to design and build robust AI solutions for lending.
AI in investments and wealth management
ScienceSoft relies on 35 years of expertise in artificial intelligence and 19 years in investment software development to design and build robust AI solutions for wealth management and investments.
AI for treatment personalization
With 35 years of experience in AI development and 19 years in healthcare IT, ScienceSoft designs secure AI-powered solutions to help healthcare providers deliver more personalized and effective care.
AI Technologies We Use
Machine Learning Methods We Rely On
Non-neural-network machine learning
- Supervised learning algorithms, such as decision trees, linear regression, logistic regression, support vector machines.
- Unsupervised learning algorithms: K-means clustering, hierarchical clustering, etc.
- Reinforcement learning methods, including Q-learning, SARSA, temporal differences method.
Neural networks, including deep learning
- Convolutional and recurrent neural networks (including LSTM and GRU)
- Autoencoders (VAE, DAE, SAE, etc.).
- Generative adversarial networks (GANs)
- Deep Q-Networks (DQNs)
- Feed-forward neural networks, including Bayesian deep learning
- Modular neural networks
ScienceSoft’s Approach to Artificial Intelligence Consulting
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Data protectionWhen building AI-powered solutions, we apply the three-pillar approach to effective data security management:
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Data qualityTo enable high data quality, we engage certified data engineers and data scientists who employ a wide set of tools to automate data validation, cleansing, and reduplication processes. |
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Guaranteed value of the AI solutionTo ensure the viability of your future AI solution, the speed and quality of the AI-enabled insights, we:
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Your Benefits from Partnering with ScienceSoft
97% of Senior Business Leaders Report Positive ROI From Their AI Investments
The figures are from the 2024 EYAI Pulse Survey that analyzed the responses of 500 executives from the senior vice president level and up. Below, you can see what business areas are positively impacted by AI and the percentage of leaders who acknowledged this influence.
Choose Your AI Service Option
An artificial intelligence consulting company, ScienceSoft provides a broad range of services from AI strategy consulting to end-to-end AI software development.
AI consulting
We introduce a tailored AI launch strategy, design the optimal architecture and tech stack for your AI solution, and assess its economic feasibility. You also get expert advice on AI security and compliance and receive a detailed project plan for risk-free AI implementation.
PoC delivery
We code and train small AI software components to prove the technical viability of the idea and avoid costly changes along the way. These proof-of-concept modules can be reused later in development to speed up delivery.
MVP development
Launching an AI MVP is a cost-effective way to roll out the software faster and start driving early payback. We can deliver an MVP of your AI solution in 3+ months, taking full charge of the app development, AI model design and implementation, and all necessary QA procedures.
Depending on your needs, we can integrate AI into your existing app or develop fully-featured AI-powered software from scratch. Our seasoned AI developers have all it takes to build industry-specific AI-powered solutions of any type and complexity and deploy them at scale.
AI model training
Our data scientists are here to help you train proprietary and open-source AI models or retrain your existing models to reach >95% output accuracy. We can compose a representative training dataset, define the appropriate hyperparameters, and tune the models to prevent under- and overfitting.
AI audit and revamp
We can perform an expert audit of your AI solution to identify the root cause of its operational issues and find pragmatic ways to fix them. Our experts can promptly upgrade the software and enhance AI models to help you generate higher value with your existing AI solution.
