TecBytz builds generative AI applications that use large language models to draft, summarise, classify and extract information, and to let people work with systems in plain language. We design the use case, connect it to your data and tools, add guardrails and human review where needed, and deploy it inside your existing applications.
What problems does it solve?
Too much text, too little time
Teams spend hours reading reports, emails and tickets to find what matters.
Repetitive writing
Drafting replies, descriptions and summaries by hand slows every process down.
Hard-to-use systems
People need training to find information that could be asked for in plain language.
What can TecBytz build?
- AI assistants and copilots: Assistants embedded in the tools your teams already use.
- Summarisation: Concise summaries of documents, meetings, tickets and reports.
- Content generation: First drafts of emails, descriptions and reports, reviewed by people.
- Classification and routing: Sort requests, messages and documents by topic, urgency or intent.
- Information extraction: Pull names, dates, amounts and entities out of free text.
- Natural-language interfaces: Ask questions of data and systems without learning a new tool.
- Conversational applications: Customer- or employee-facing chat grounded in approved content.
Where can it be applied?
Potential applications
Customer service drafting
Suggested replies based on the ticket history and your knowledge base, approved by an agent.
Report summarisation
Daily or weekly summaries of operational reports for managers.
Natural-language search
Staff ask a question and get the relevant records instead of building filters.
Which systems does it connect to?
- CRM and helpdesk tools
- Document stores and intranets
- Email and collaboration tools
- Your web and mobile applications
We integrate through your systems' APIs, databases and extension points. See AI integration.
How do we deliver it?
Discover
Understand the business problem, data, users and desired outcomes.
Assess
Evaluate data readiness, existing systems, integration requirements, security and AI feasibility.
Design
Design the AI architecture, user experience, workflows and integration model.
Develop
Build, integrate and test the AI-powered solution.
Validate
Evaluate accuracy, reliability, security, performance and user experience.
Deploy
Deploy into your environment and integrate with existing systems.
Improve
Monitor usage, collect feedback and keep improving the solution.
Questions
Will our data be used to train public models?
We design solutions so your data is used only to serve your requests, and we choose model providers and deployment options that match your data-protection requirements. Where needed, solutions can run in your own cloud environment.
How do you stop the AI from making things up?
We ground answers in your approved content, limit the model to defined tasks, show sources where relevant, and add human review for anything customer-facing or high-impact.
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