GENERATIVE AI FOR IT & ENGINEERING
Optimize software development and accelerate innovation with GenAI
Streamline software development, testing, deployment, and operational workflows
Build tomorrow’s innovations, today
IT & engineering teams face a broad range of challenges as they scale and compete in today’s highly dynamic market
It's becoming harder to manage complex systems, which leads to more time spent fixing errors and a higher risk of defects.
To deliver products faster, companies often sacrifice thorough testing and security, creating a constant tradeoff between speed and quality.
Technical debt makes it harder to create new features, opens up security risks, and prevents companies from using modern development methods.
Teams often face skill gaps, making it difficult to adopt cutting-edge solutions, implement new methodologies, or address specialized technical demands.
GENAI FOR IT & ENGINEERING
Transform IT & engineering with GenAI
Vertesia’s cutting-edge generative AI solutions are built to elevate your IT and engineering operations, empowering your teams to focus on innovation and core development.
Write code faster
Enhance testing & find bugs
Improve quality assurance (QA)
Simplify documentation
Optimize support
Innovate quickly
Hashgraph automates their software development lifecycle with Vertesia
Hashgraph develops the software that powers Hedera, a high-performance public network used for building decentralized services, including digital payments, asset tokenization, and smart contracts
See how we could help you achieve similar results
Proven use cases for IT & engineering
These solutions have been developed in partnership with IT and engineering leaders to ensure they deliver measurable ROI, integrate seamlessly with existing development solutions and infrastructure, and are highly secure and compliant.
Intelligent code generation
Automated QA test cases
Proactive threat detection
Support ticket summarization and routing
Release notes and product documentation generation
Personalized learning and skill development
24/7 support agents
Predictive maintenance for IT systems
Autonomous bug fixing and remediation
IT performance reporting and trend analysis
Proactive project risk identification
Skills matching and gap analysis
Generate release notes and product documentation
It's a struggle to write clear release notes, create complete product instructions, and effectively tell people about new updates and features.
Step 1: Gather and Analyze Information
Ingest all existing technical documentation, code repositories, and data from project management software into the Vertesia platform. We use Large Language Models (LLMs) to analyze this information, discover key features, changes, and bug fixes, and then extract the important details.
Step 2: Simplify and Translate Content
LLMs can automatically write release note drafts. For product documentation, the LLMs simplify technical jargon and rewrite long paragraphs into clear, simple language that everyone can understand. LLMs can also translate these documents into different languages, ensuring a global reach.
Step 3: Deliver Personalized Content
The Vertesia platform delivers the new documents in multiple formats, like help articles, knowledge base entries, or even in-context help within an application. LLMs can also customize the information for different types of users, ensuring the right information gets to the right person.
Write code and collaborate effectively
Maintaining code quality which accelerating development cycles in a collaborative environment can be a significant challenge. Manually reviewing and testing code often take a lot of time, causing delays and possible mistakes.
Step 1: Analyze Code and Make Suggestions
Analyze code as it’s being written. AI finds potential mistakes, security risks, and style problems. It then offers intelligent suggestions to make the code better and more consistent.
Step 2: Automate Code Reviews and Testing
Automatically review code. LLMs find possible issues, suggest improvements, and point out serious security risks or vulnerabilities. This helps speed up the development process and lowers the chance of errors.
Step 3: Collaborate and Share Knowledge
Our low-code platform enables multiple teams to easily create, test, and deploy AI apps and agents which means everyone can use the platform, making it simple for developers to work on code together and share what they've learned.