Reshaping today's business with AI services.
Schedule Free Consultationof executives see AI as a key advantage for improved decision-making.
In today's dynamic business landscape, AI is no longer a luxury; it's a necessity for staying competitive. With over 25 years of experience in digital product engineering, Coherent Solutions offers cutting-edge AI consulting and development services, ensuring that your organization not only embraces AI but also excels in the AI-driven era.
Guiding organizations across AI maturity levels, we collaborate on impactful use cases and demonstrate transformative AI potential through Proof of Concept initiatives.
From concept to final product, we develop and integrate cutting-edge AI solutions into your business operations, elevating efficiency and enhancing overall business performance.
Boost operational efficiency and optimize expenses by integrating intelligent monitoring and predictive maintenance into your operational workflows.
We are experts in digital product engineering, with over 25 years of delivering measurable impact on business success for our clients.
With 1000+ successful projects, our track record speaks for itself. We consistently deliver AI services that exceed expectations.
Our AI development team comprises over 50 highly skilled experts proficient in key AI and ML technologies and platforms.
As a trusted AI services provider, we’ve successfully served clients across a wide range of industries, including finance, retail, healthcare, and manufacturing.
At Coherent Solutions, we offer the technical expertise and industry experience necessary to develop digital products faster and at unrivaled quality. Reach out to us today to discover how our experts can help your business find its competitive edge.
NLP and Text Processing
Our expertise in Natural Language Processing (NLP) and Text Processing opens doors to effective communication, sentiment analysis, and content comprehension. Within the NLP and Text Processing domain, our proficiency is reflected through:
-Scoring Search Results: BoW, TF-IDF, SVM, LSTM.
-Recommendations: word2vec, doc2vec, RNN Attention.
-Finding vulnerabilities in source code: Encoder-Decoder seq2seq, LSTM.
-Sentiment Analysis: LSTM, NN Transformer.
-Topic Modeling: LDA, top2vec, BERTopic.
E-commerce Analysis
By leveraging our advanced forecasting models, organizations can make informed, data-driven decisions, optimize supply chains, and thrive in the highly competitive e-commerce landscape. Within the E-commerce/Forecasting domain, our tailored tools include:
-Customer Segmentation: Clustering, K-Means, DBSCAN, and more.
-Lead Scoring: Linear Regressor, Random Forest, and Boosting Regressors.
-Customer Support: ARI, Silhouette Coefficient.
Computer Vision
Coherent is at the forefront of image processing and computer vision technologies, driving innovation in areas such as object recognition, autonomous systems, and visual analytics. Our expertise is backed by a sophisticated set of tools designed specifically for diverse tasks:
-Object Detection and Extraction: CNN, RNN, R-CNN, ConvLSTM.
-Object Tracking: R-CNN, DeepLab, CNN (Yolo).
-Object Segmentation: UNet, Mask R-CNN+, AdaptNet.
-Face Swap: CNN, GAN (DeepFake), Transfer Learning.
-Face Recognition: CNN (Yolo), Transfer Learning.
Generative AI
As a trusted AI services company, we’re proficient in Generative AI, helping businesses transform their processes with innovative and dynamic solutions. In this cutting-edge domain, we navigate through four key pillars:
-Model Fine-tuning: Instructions, PEFT, LoRA, QLoRA.
-RAG (Retrieval Augmented Generation): LLamaIndex, LangChain, DuckDB, ChromaDB.
-Custom Large Language Model (LLM) Chains: LangChain, LlamaIndex, OpenAI, DocTran, HF Transformers, WhisperX.
-Chat Bots: LangChain, LLamaIndex.
AI/ML can benefit businesses and organizations in a number of ways. It can automate repetitive tasks, improve efficiency and accuracy, enhance decision-making with data-driven insights, personalize customer experiences, optimize processes, detect anomalies or fraud, and enable predictive maintenance, among many other applications.
To get started with implementing AI/ML in your business, you can follow these steps:
-Identify a specific problem or opportunity where AI/ML can add value.
-Gather and prepare relevant data for training and testing
-Select appropriate AI/ML techniques and algorithms based on your problem.
-Train and evaluate models using the data.
-Implement the model into your business process or application.
-Continuously monitor and refine the model as needed.
The data needed to train AI/ML models depends on the specific problem and the type of algorithm being used. In general, you need labeled data that represents the patterns or behaviors you want the model to learn. The quality, quantity, and variety of the data are critical to model performance.
The time required to develop and deploy an AI/ML solution varies widely depending on factors such as project complexity, available resources, team expertise, and data availability. It can range from a few weeks for simpler models to several months for more complex projects. Iterative development and continuous improvement are common in AI/ML projects.
The amount of data required for effective AI/ML models depends on the complexity of the problem and the algorithms chosen. While more data generally leads to better models, it’s possible to train effective models with smaller data sets using techniques such as transfer learning or data augmentation.
Yes, AI/ML integrates with existing systems and technologies. APIs and libraries provided by AI/ML frameworks allow for easy integration, and models can be deployed on cloud platforms or embedded in existing software solutions.
Selecting the right AI/ML tools and platforms depends on your specific needs, such as problem domain, available data, scalability requirements, and budget. As an experienced artificial intelligence services company, we first evaluate factors such as ease of use, community support, available resources, and integration capabilities when choosing the most appropriate tools and platforms.
AI/ML has many real-world applications across industries. Some examples include:
-Natural language processing for chatbots and virtual assistants.
-Image and video recognition for autonomous vehicles, surveillance, and medical imaging.
-Fraud detection for financial transactions.
-Personalized recommendations in e-commerce and content streaming platforms.
-Predictive maintenance in manufacturing and asset monitoring.
-Drug discovery and genomics research in healthcare.
Simply fill out our contact form below, and we will reach out to you within 1 business day to schedule a free 1-hour consultation covering platform selection, budgeting, and project timelines.