LLM-Powered Custom AI Agents
Build custom AI agents trained on your processes. Deploy secure, optimized solutions like dev copilots and support assistants tailored to teams.
Why Custom AI Agents Are Important
Most AI products that you can buy already have training for general talks. But agents that really provide value to your business are those that:
That's what makes a chatbot different from a real agent.
What does Improwised Technologies offer for making custom agents?
Designing agents and mapping out workflows
To figure out what the agent should do, we start by mapping out your workflows, which include tasks, inputs, user roles, and edge situations.
Choosing and Fine-Tuning the LLM
We employ open-source models (like LLaMA and Mixtral) or private APIs and then fine-tune them with your data, depending on your privacy and financial demands.
Putting knowledge sources into use
We use vector embeddings to construct semantic search layers for your agents so they can understand internal material like docs, databases, tickets, and wikis.
Interfaces for Natural Interaction
We make interfaces that work with how your teams already talk to each other, whether it's through chat, email, the command line, or Slack. They also have contextual memory and follow-up handling.
Deployment with Privacy First
Agents can run on your private AI server lab (see the previous page) or in secure containers. No data will be shared with anybody outside of your organization.
Loops of feedback and iteration
We keep track of interactions, failures, and user input so that we can keep retraining the agent and making it more useful over time.
What This Gives You
Faster times for support to fix problems
Better automation for both technical and non-technical jobs
Better use of internal documents and data
Less time spent training new employees
Why should you choose Improwised Technologies for Agentic AI?
We don't just send agents out; we also assist you in designing the perfect ones based on how your business works. Improwised gives your agents more clarity in engineering, more knowledge of security, and the chance to improve them over time.
- Not tech-first, but workflow-first
- Full-stack development including AI, UI, and infrastructure
- Domain context and user experience design
- Improvement that can be measured after deployment
We make sure that your AI agents really help and don't just talk.
Frequently Asked Question
Get quick answers to common queries. Explore our FAQs for helpful insights and solutions.
Not Sure What an AI Agent Could Do for You?
Let's look at several examples of how to use it, from support ticket summaries to research assistance inside the company. An AI agent can certainly help if it's something that happens a lot and has a lot of text. We'll show you how.