AI Services

Why Choose Coherent Solutions

  • Expert Digital Engineering

    We are experts in digital product engineering, with over 25 years of delivering measurable impact on business success for our clients.

  • Proven Track Record

    With 1000+ successful projects, our track record speaks for itself. We consistently deliver AI services that exceed expectations.

  • Comprehensive Tech Stack

    Our AI development team comprises over 50 highly skilled experts proficient in key AI and ML technologies and platforms.

  • Industry Experience

    As a trusted AI services provider, we’ve successfully served clients across a wide range of industries, including finance, retail, healthcare, and manufacturing.

Need Help With Your Project?

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.

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Our Expertise

NLP Text Processing E-commerce Analysis Computer Vision Generative AI

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.

NLP Text Processing

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.

E-commerce Analysis

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.

Computer Vision and ImageVideo processing.png

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.

Generative AI

Our Approach

At Coherent, we don't just view artificial intelligence as a single capability; instead, we adopt a comprehensive five-stage AI maturity model that encompasses five essential dimensions:

  • Exploring

    • Strategy: Aligning your organization's structure and business goals to drive AI initiatives forward.
  • Implementing

    • Data: Ensuring the availability of high-quality data for training, running, and improving AI models.
  • Operationalizing

    • Technology: Providing the necessary tools, infrastructure, and workflows to execute AI projects effectively.
  • Scaling

    • People: Equipping engineering teams with the right roles, skills, and training to build AI solutions while empowering business teams to leverage AI effectively.

    • Governance: Establishing policies, procedures, and processes to ensure the responsible and ethical applications of AI within your organization.

FAQ

  • How can AI/ML help my business or organization?

    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.

  • How can I get started with implementing AI/ML in my business?

    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.

  • What data is needed to train AI/ML models?

    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.

  • How long does it typically take to develop and deploy an AI/ML solution?

    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.

  • Do I need a large amount of data to train an effective AI/ML model?

    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.

  • Can AI/ML be integrated with existing systems and technologies?

    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.

  • Can you help me choose the right AI/ML tools and platforms for my specific needs?

    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.

  • What are some of the real-world applications of AI/ML?

    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.

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Here's what happens next:

  1. Our sales rep will contact you within 1 day to discuss your case in more detail.
  2. Next, we will arrange a free 1-hour consultation with our experts on platform selection, budgeting, and timelines.
  3. After that, we’ll need 1-2 weeks to prepare a proposal, covering solutions, team requirements, cost & time estimates.
  4. Once approved, we will launch your project within 1-2 weeks.