Custom AI agents
Generic AI tools waste your time pretending to save it.
We build custom AI agents that work like part of your team from day one.
SOLVE
What Business Problems Can a Custom AI Agent Solve?
Ever feel like your team spends more time chasing tasks than making meaningful progress?
Fixing Operational Bottlenecks and Manual Work
→ Custom AI agents for businesses handle recurring workflows automatically, reducing manual effort and freeing teams to focus on higher-value work.
→ AI agents act as real-time assistants, surfacing the right information instantly – whether it’s policy rules, project status, or past decisions.
→ Custom AI agents integrate with your tools to manage workflows, send nudges, and make sure nothing slips through the cracks.
Improving Services and Customer Experience at Scale
→ Custom AI agents for services give customers fast, consistent support 24/7, trained on your actual knowledge base.
→ AI agents resolve these instantly – reducing tickets, holding times, and burnout.
→ AI agents work across departments, giving everyone access to up-to-date, unified customer information.
PROCESS
How to Make a Custom AI Agent (our way)
Building a custom AI agent requires more than just plugging in an existing model – it involves deeply understanding your business logic, connecting the right data sources, designing intelligent workflows, and testing an agent to behave reliably in real-world conditions. Off-the-shelf tools don’t know your processes, language, or goals. Getting an AI agent to align with all three takes careful planning, integration, and iteration. Whether you need a personal assistant, a support agent, or a task automation system, the process starts with a clear understanding of your needs and ends with a reliable, real-time digital coworker. Here’s how we design custom AI agents to work within your business processes, not around them.
Before we build, we listen. The first step in how to create custom AI agents is understanding your business context. What’s the pain point? Where does your team lose time, accuracy, or control? Is it repetitive data entry, customer inquiries, or coordination between tools? At this stage, we map out clear tasks the agent should handle, who it will support (customers, employees, or both), and what “success” looks like. Whether you're building an AI personal assistant or a back-office processor, clarity here ensures the agent does the job right – and only the job you actually need.
Once the goals are clear, the next step is technical integration. The agent is connected to your existing platforms, such as CRMs, ERPs, ticketing systems, or shared drives. We also decide how the agent will communicate – through chat, email, or directly inside your product. This is also when we train the agent on your data. That could include policies, documents, historical chats, spreadsheets, or product manuals. Instead of using generic knowledge, the agent learns from your specific environment, making it more accurate and relevant. When integration is done correctly, your team members can start using the AI agent right away without a long onboarding process. We aim to make it a part of everyday work that doesn’t require extra time for managing.
After setup and testing, the AI agent goes live. We usually begin with a small rollout and closely monitor how it performs. The agent’s behavior is refined based on real interactions and your team’s inputs, so it becomes more accurate over time. Once stable, the agent can be scaled across teams or expanded to handle more use cases. The final result? A reliable system that doesn’t just automate tasks, but supports your business in real time.
OUR CLIENTS
Clients who use custom AI agents
BENEFITS
Benefits of Using Custom AI Agent
Use Cases of Custom AI Agent
When you build a custom AI agent, you’re not adopting a general tool – you’re creating a solution that works exactly the way your business does. Whether you need to automate internal processes, speed up support, or connect systems, the results speak for themselves.
Here are real-world use cases for custom AI agent solutions, built and deployed to solve high-impact challenges.
Engineers were constantly searching across Confluence pages, codebases, and Slack threads to find answers or past solutions. Valuable knowledge was scattered and hard to reuse.
Solution
The company deployed a custom AI agent trained on internal documentation and past conversations. Engineers could query it in natural language to retrieve code snippets, architecture diagrams, or decisions.
Result
- Reduced time spent searching for information
- Better onboarding for new engineers
- Improved consistency across teams
Junior lawyers spent hours reviewing case law, filtering irrelevant results, and compiling findings into briefs. This slowed down project timelines.
Solution
A custom AI agent was trained on legal databases, internal memos, and case summaries. Its task was to filter, summarize, and rank relevant legal material based on the query context.
Result
- Research time cut by half
- More accurate first drafts of legal briefs
- Senior staff could focus on strategy, not preliminary work
Editors were spending too much time manually reviewing articles for tone, consistency, formatting, and fact alignment. The team struggled to keep up with tight publishing deadlines while maintaining quality.
Solution
After training on brand guidelines, past published content, and internal editorial rules, AI agent could pre-scan articles before human review. By flagging tone mismatches, formatting issues, overused phrases, and possible factual discrepancies, it took away the routine tasks of the editors.
Result
- 40% reduction in time spent on content review
- Fewer edits required after publishing
- More consistent tone and style across all contributors
Coordinating logistics, outreach, and updates across multiple teams for recurring events was time-consuming. Staff had to manually track contractors confirmations, volunteer shifts, marketing deadlines, and venue requirements – often in spreadsheets and email chains.
Solution
A custom AI agent was developed for the organization to act as a central coordinator. It automatically gathered updates from calendars, emails, and shared documents, providing teams with timely reminders, up-to-date task statuses, and alerts when deadlines were at risk.
Result
- 60% reduction in coordination-related emails
- Fewer missed deadlines and last-minute issues
- Volunteers and staff received timely, relevant updates without manual follow-up
FAQS
FAQs about custom AI agents
These agents are trained on your unique materials, such as documents, policies, or historical data. As a result, their output is accurate, relevant, and aligned with your operations. If you feel that available AI agents don’t fit your organization’s needs, custom AI agent is a way to go.
Each agent is trained using your data and logic, so it doesn’t rely on generic assumptions (like those used by general-purpose language models trained on public internet data). The agent works in real time, learns from interactions (when needed), and delivers results with minimal manual oversight. The development process typically includes goal setting, integration, testing, and continuous learning and improvement after launch.
Unlike hiring additional staff, a custom AI agent can scale instantly without adding cost per task. Over time, the improvement in efficiency and precision in all the organization will show tangible results – some financial, others reflected in faster delivery, fewer errors, and a more focused, less overwhelmed team.