AI agents that do real work for your business.
We build AI agents for business: assistants that don't just answer, but take the next step. They book, sort, fill in and follow up inside the tools your team and customers already use, with people checking the work that matters.
Senior engineers build every agent. We'd rather automate one task properly than ten badly.
For businesses with repetitive work and a clear finish line.
Agents pay off fastest in one of three places.
Customers wait on your team for simple things
Booking, rescheduling, checking what's available. The assistant we built for AskEddy takes travelers from finding an activity to booking it in one conversation.
Your team re-types the same data every day
Copying details from emails, messages, receipts or PDFs into another system. An agent reads them, fills in the record, and flags anything it isn't sure about.
Work piles up between your tools
Checking one system, updating another, chasing a reply. An agent handles the routine path and hands the unusual cases to a person, with the context attached.
Good fit if
- Your team repeats the same lookups, emails or data entry every day
- You want AI inside a product you already run
Not a fit if
- You want a new AI model trained from scratch
- There's no clear task for the AI to do yet
What our AI agent development covers.
An agent is AI with access to your tools and a clear job. Here's what goes into one you can trust with real work.
Assistants your customers talk to
On your website, WhatsApp or Telegram. They understand plain requests, check live information and finish the task, rather than pointing to a form.
Under the hood- Conversational AI
- WhatsApp / Telegram
Agents your team hands work to
Reading incoming messages, documents and receipts, then sorting them, filling in records and drafting replies for a person to approve.
Under the hood- Document processing
- LLM integrations
Connected to your real systems
Agents act through the same tools your team uses, like bookings, orders or your database, with access limited to exactly what the job needs.
Under the hood- Tool calling
- API integrations
People in the loop where it matters
Clear rules for what the agent does alone, what it asks about and what it hands over. Anything risky waits for a person.
Under the hood- Approval flows
- Escalation
Plain automation around it
Not every step needs AI. We use ordinary automation for the predictable parts and save AI for the steps that need judgment, which keeps it fast and cheap to run.
Under the hood- Workflow automation
- Webhooks
A record of everything it did
Every action logged, so you can see what the agent did and why, measure how often it gets it right, and improve it.
Under the hood- Logging
- Evaluation
Need AI that answers from your documents or powers a feature in your product? See AI integration.
Agents and automation we've built.
How an agent project runs.
We automate one task end to end, prove it saves time, then widen it.
Discovery sprint
One week to choose the first task, map every step and exception, and decide what the agent may do on its own. The plan is yours either way.
Plan
A signed scope with a fixed price per milestone, and a point after each milestone where you can stop.
Build
Short cycles with a working agent to try every week, tested on your real requests and documents.
Launch
A careful rollout: the agent drafts and a person approves until the numbers show it can work alone. Monitoring and a rollback plan included.
Grow
More tasks once the first one pays off, tuning from real usage, and optional managed hosting on AWS or GCP.
Discovery sprint
- Price
- Quoted upfront
- Length
- 1 week
One focused week before any build. We dig into your idea or your system, find the risks early, then hand you a plan you can act on, with us or without us.
- An architecture plan written in plain language
- Scoped milestones with time and cost estimates
- The main risks and how we'd handle them
- A roadmap you keep, whether or not you continue with us
AI agent questions.
What is an AI agent?
An AI agent is AI that can take actions, not only answer. A chatbot tells a customer how to book; an agent checks what's available and makes the booking. It works through the same tools your team uses, within limits you set.
What tasks are AI agents good at today?
Work with a clear goal and a clear way to check it's done: bookings, answering questions from your own information, reading documents and filling in records, sorting and routing requests, drafting replies. They're weaker at open-ended judgment calls, which is why we keep people on those.
Will an AI agent replace my team?
That isn't how we build them. Agents take the repetitive part of the work so your team can spend its time on the cases that need a person. Anything unusual or risky is handed over, with the context attached.
How do you stop an agent from making mistakes?
It only gets access to what the task needs, it asks or hands over when it isn't sure, and risky actions wait for a person to approve. Every action is logged, and we measure accuracy on your real requests before it works alone.
Can an agent work inside WhatsApp?
Yes. TallyMsg works entirely through WhatsApp and Telegram messages, photos and voice notes. An agent can live wherever your customers or team already talk: your website, WhatsApp, Telegram or email.
Are you an AI automation agency?
In the sense that we automate work with AI, yes. The difference is how: senior engineers build every project, we build on your own systems instead of off-the-shelf templates, and you own everything we build.
How much does an AI agent cost?
We quote a fixed price per milestone, agreed before work starts. It depends on how many systems the agent connects to, how many exceptions the task has, and how much checking it needs. The discovery sprint turns that into scoped milestones, and the plan estimates what the agent will cost to run each month.
Further reading
Got work that keeps repeating?
Tell us the task and the tools it touches. We reply within one working day.