About Ogiven

Frequently asked questions

• How does Ogiven help?

  Ogiven leverages AI to help deliver high-quality software with fast turnarounds and competitive pricing—saving you time, reducing costs, and driving your success.

• Does Ogiven use open-source AI LLMs?

  We give our clients the choice of building their AI agents with closed and open-source modals.

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• Can Ogiven work with an existing codebase, or do you only build from scratch?

  Whether you need us to work with your existing codebase to enhance, fix, or scale it, or build a brand-new solution from scratch, we’ve got you covered.

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• Do you provide free consultations or estimates before starting a project?

  Yes, schedule a call for a free consultation.

  Schedule Call➔

• What happens if the project goes over budget or schedule?

  All projects are priced at the start of the agreement based on a specific budget and a timeline planned with the steps from Ogiven Software development process to ensure all unexpected delays are anticipated.

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• Can we track the progress of our project in real time?

  Yes, project progress can be viewed in the client portal, clients have the options to select scheduled progress reports that include working demostrations of the software or app.

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• Can you explain how your AI solutions handle data privacy and compliance (e.g., GDPR, HIPAA)?

  Ogivens AI solutions are designed with data privacy and compliance as top priorities. We follow strict protocols to ensure all data is handled securely and in accordance with regulations.

  1. Data Encryption: We use advanced encryption methods to protect sensitive data during storage and transmission.
  2. Access Control: We implement robust authentication and authorization mechanisms to ensure only authorized personnel can access the data.
  3. Anonymization: When possible, we anonymize or pseudonymize data to safeguard individual identities.
  4. Regulatory Compliance: Our team stays up-to-date with the latest privacy regulations and ensures that all AI models and workflows align with these standards.
  5. Audit Trails: We maintain detailed logs and audit trails to track data usage and identify any unauthorized access.
  6. Client-Specific Policies: We customize our compliance measures to meet the unique requirements of each client's industry and geography.

• Can AI solutions integrate with our existing systems and tools?

  Yes, Ogiven AI solutions are designed to seamlessly integrate with your existing systems and tools. Here's how we ensure a smooth integration process:

  1. Compatibility Analysis: We assess your current systems and tools to ensure compatibility and identify the best integration approach.
  2. API Integration: Our AI solutions can connect to your systems using APIs, enabling smooth data flow and communication.
  3. Custom Adapters: If needed, we develop custom adapters or middleware to bridge the gap between our AI solutions and your tools.
  4. Scalability: We design our AI solutions to scale alongside your systems, ensuring long-term compatibility and growth.
  5. Testing and Validation: Rigorous testing is conducted to ensure the integration works flawlessly without disrupting your existing workflows.
  6. Ongoing Support: Post-integration, we provide support to monitor performance and make adjustments as needed.

• What technologies and programming languages do you use?

  Ogiven has broad expertise that allow us to choose the right tools for your specific needs, whether you're looking for a robust web application, mobile application, AI-driven insights, or scalable backend systems.

  1. Programming Languages:
     1. JavaScript/TypeScript: For building web applications, APIs, and scalable solutions.
     2. Python: Ideal for AI, machine learning, and data-driven applications, leveraging frameworks like TensorFlow, PyTorch, and Scikit-learn.
     3. Java: Used for robust enterprise-level applications and backend services.
     4. Go (Golang): For performance-critical, scalable backend services.
     5. R: Specialized for statistical analysis and data visualization in AI-related projects.
  2. AI Technologies and Frameworks:
     1. TensorFlow and PyTorch: For deep learning and building complex neural networks.
     2. GPT, DeepSeek, Gemini and Llama For natural language processing, chatbots, and conversational AI.
     3. Hugging Face Transformers: To build state-of-the-art NLP models like text summarization and translation.
     4. Scikit-learn: For traditional machine learning algorithms.
     5. Keras: To simplify deep learning model development.
     6. Amazon SageMaker, Google Vertex AI, Azure AI:For deploying and managing AI/ML models in the cloud.
  3. Frontend Technologies:
     1. React.js: For building interactive and dynamic user interfaces.
     2. Next.js: For server-rendered web apps with exceptional performance.
     3. Tailwind CSS: For creating modern, responsive designs.
  4. Backend Technologies:
     1. Node.js: For building scalable and efficient backend APIs.
     2. Django and Flask: Python frameworks used for AI-powered applications and REST APIs.
     3. Spring Boot: For creating enterprise-grade Java applications.
  5. Cloud and DevOps:
     1. AWS, Google Cloud, Microsoft Azure: For scalable and reliable cloud infrastructure.
     2. Docker & Kubernetes: To containerize and manage applications efficiently.
     3. CI/CD Pipelines: Using Jenkins, GitHub Actions for seamless development and deployment.
  6. Databases:
     1. PostgreSQL and MySQL: For traditional relational databases.
     2. MongoDB: For flexible, NoSQL data storage.
     3. Redis: For caching and real-time data processing.
  7. Data and Analytics:
     1. Pandas and NumPy: For data analysis and processing.
     2. Power BI, Tableau, and Looker: For data visualization and business intelligence.