AI agent development
Custom AI agents that handle real work.
An AI agent is software that understands a request, looks up the information it needs, and takes approved actions in your systems: replying to a customer, updating a record, booking a slot, or preparing a draft for a person to approve.
We design agents around one clear job, connect them to the tools you already use, and give them only the permissions that job needs. The goal is simple: fewer repetitive tasks for your team, faster answers for your customers.
What you get
- A working agent, not a demoConnected to your real data and systems, tested against real cases before launch.
- Clear limitsDefined actions, permissions and escalation rules, so the agent never goes beyond its job.
- Human handoverWhen it is unsure or the stakes are high, it hands over to your team with full context.
- Measurable resultsDashboards and logs showing what the agent handled, how well, and what it cost.
Where it helps
- Customer inquiry handlingAnswers common questions from your website, email or chat using your own policies and product information.
- Lead qualificationAsks the right questions, scores the lead and routes it to the right person with a summary.
- Internal knowledge assistantLets your team ask questions about SOPs, policies and past documents and get answers with sources.
- Appointment coordinationFinds suitable slots, books and reschedules, and sends reminders through your calendar tools.
- Document processingReads invoices, forms or resumes, extracts the fields you need and flags anything unusual.
- CRM updates and follow-upsLogs conversations, updates deal stages and drafts follow-up emails for approval.
- Order and status questionsLooks up orders or tickets in your system and gives customers accurate, current answers.
- Workflow assistancePrepares drafts, checklists and reports so your team reviews instead of starting from scratch.
How we build it
- 01 DiscoverWe map the job the agent will do, the systems it touches, and what a good outcome looks like.
- 02 DesignWe define its tools, permissions, data sources, guardrails and when it must hand over to a person.
- 03 BuildWe connect it to your systems, write and test prompts, and evaluate it on real examples.
- 04 DeployIt goes live with monitoring, logs and a simple way for your team to review its work.
- 05 ImproveWe review failures and costs and keep improving accuracy as real conversations come in.
AI isn't finished at launch. Every system we ship is evaluated and monitored in real use.
Safeguards, built in
- Least-privilege accessThe agent can only read and change what its job requires.
- Approval for high-impact actionsRefunds, payments, deletions and similar actions wait for a human yes.
- Grounded answersAnswers come from your approved sources, and the agent says when it does not know.
- Full audit trailEvery action is logged, so you can see what happened and why.
What we build with
AI and LLMsOpenAI API (GPT-4o runs in production in Vikku Labs' own products), structured outputs, prompt and evaluation pipelines; other models when a project needs them
AutomationAPI integrations, webhooks, scheduled jobs, transactional email, event-driven workflows
EngineeringReact, Next.js, TypeScript, Node.js, Python, PostgreSQL, MongoDB, Supabase, AWS, Vercel, Docker, React Native
See our AI in action: try the AI Visibility Score or the AI Project Planner, both running GPT-4o in production.
Frequently asked questions
What is the difference between an AI agent and a chatbot?
A chatbot mostly answers questions. An AI agent can also take actions in your systems, such as updating a CRM record, booking an appointment or creating a ticket, within the permissions you give it.
Will an AI agent replace my team?
No. Good agents take over the repetitive part of a job, like answering the same questions or copying data between tools, so your team spends its time on the work that needs judgment. High-impact decisions stay with people.
Which tools can an agent connect to?
Anything with an API: CRMs, help desks, calendars, email, spreadsheets, databases and your own internal systems. During discovery we check exactly what your tools allow.
What happens when the agent gets something wrong?
We design for it. Agents are tested before launch, unsure cases are handed to a person, high-impact actions need approval, and every action is logged so mistakes are visible and fixable.
How much does it cost?
It depends on scope: how many workflows, systems and users are involved, and how much accuracy and oversight the work needs. Every project starts with a free discovery call, and you get a written scope and estimate before anything is built. For a quick ballpark, try our free Project Estimator.
Is our data safe?
We use your data only for your project, give each system the minimum access it needs, and keep secrets on the server, never in the browser. By default, data sent through the OpenAI API is not used to train OpenAI's models. If your data is sensitive, we design around it from day one, for example by masking personal details before they reach a model.
Who owns the code and the system?
You do. You get full ownership of the source code, prompts, configuration and documentation, handed over in your own repository.
Do you support it after launch?
Yes. AI systems need monitoring: we track quality and cost, fix failures and improve prompts and workflows as real usage comes in. Most clients stay on a light monthly retainer after launch.
Related services
Tell us what you want AI to do.
Book a free AI discovery call. We'll tell you honestly whether AI is the right fit, and what the practical next step is.