AI agent development that starts with one real task
Much of your team’s day is a chain of small steps: read the email, find the order, check the policy, update the system. We build AI agents that do that chain, show every step they took and ask a person before anything risky.
What an agent project covers, from mapping the task to monitoring after launch. If you need something that isn’t on the list, we’ll say so before we start.
An agent pays off when a job has several steps, needs information from more than one system and takes a person's time today. If the job is only answering questions, AI chatbot development is simpler and cheaper.
Support and order follow-up
Reads the customer's message, checks the order and stock, drafts the reply and asks a person to approve the refund.
Inbox triage and routing
Reads incoming email, classifies it, creates the ticket or task in the right system and replies when the case is routine.
Research and reporting
Gathers information from the web and your documents and writes a sourced brief or the weekly report.
Monitoring and alerts
Watches sales, stock or ticket queues and acts or alerts a person when something drifts from normal.
Back-office operations
Creates records, updates statuses and reconciles data between systems that do not talk to each other.
Internal IT and HR requests
Handles access requests, onboarding checklists and routine questions, and escalates what needs a decision.
Control and safety
An agent you can trust with real work
After "can it do it?" comes "what if it gets it wrong?". These are the safeguards we build into every agent.
Payments, deletions and customer messages wait for a person's OK.
Least-privilege access
The agent gets only the tools and data its job needs, with its own credentials.
Every action logged
A full record of what the agent did and why, so you can audit and fix.
Limits on cost and scope
Caps on spend, steps and actions per run stop a confused agent early.
How we work
How an AI agent project works with us
Not every task needs an agent. If a simple AI automation does the job, we tell you.
Choose one task
We pick the job with the clearest value and map the steps, the systems it touches and the cases that need a person.
Build a supervised prototype
A working agent that proposes every action, so you see how it reasons on your own data.
Test on past cases
We replay real cases, measure success rate and cost per task, and fix the weak spots before anything goes live.
Launch with guardrails, then widen
The agent goes live with approvals and limits. As it earns trust, we raise its autonomy or add the next task.
Technology
Technology behind our AI agents
We choose per task. These are the tools we know well.
Language models
OpenAI GPT
Anthropic Claude
Google Gemini
Llama
Mistral
Agent frameworks
LangGraph
MCP
LlamaIndex
custom Python
Systems it connects to
Email and calendar
CRM
ERP
Shopify
helpdesks
your own APIs
Approvals and alerts
Slack
Microsoft Teams
email
your own dashboard
Hosting
Azure
AWS
Google Cloud
your own servers
Engagement models
Ways to work with us on AI agents
Start with one task at a fixed price, give your agents more work month by month and keep them reliable after launch. You always talk to the people who build your agent.
Fixed-price agent project
Most common
A four-week pilot on one real task, then more phases, each scoped and priced before it starts.
Softclaire is development company unlike (many) others. Friendly and flexible, good with deadlines and trustworthy. Experts in multiple fields. We are very happy to work with them as development partner. Very much recommended!
We have been working with Softclaire for almost 2 years now, on our main product - an online gaming website, play-games.com. Being in the web games niche, things change fast so we need to adapt on the go - and we can trust them with this. They are easy to work with, proactive, and manage work flow very well. We value their transparency and their perseverance in every task they undertake.
We approached Softclaire with nothing more than an idea and a few initial mockups for our SaaS product. Their team stepped in guiding us through strategic planning, development and devops. We are still working with them for ongoing maintenance and feature updates. If you're looking for a reliable, long-term technical partner, I highly recommend them.
Within 6 months of our app launch we have gained 750 users. We have had a huge boost in traffic on the platform since launch and have multiple 5 star ratings on the App Store. We have also had comments from other software developers commenting on how brilliant the app is structured.
The team delivered everything on time and provided a mind map to showcase the progress. Overall, they were very flexible and committed to meeting expectations.
We had an idea for a tech startup in the medical niche, but we lacked the expertise to design and develop a product of this scale. Thankfully we found an amazing team that guided us through the process every step of the way.
A few months ago, I contacted them for a custom Perfex CRM module and the e-Invoice module. Their work is of exceptional quality, and I am extremely satisfied with both the quality and the budget. I highly recommend Softclaire to all businesses and investors!
What is an AI agent, and how is it different from a chatbot?
A chatbot answers questions. An AI agent is given a goal and works towards it: it plans the steps, uses tools such as your email, CRM or ERP, checks the results and continues until the task is done. If you only need answers for customers, see AI chatbot development; if you want answers for your team from your documents, see AI assistant for business.
What tasks are a good fit for an AI agent?
Tasks with several steps, information spread across systems and a clear result, such as order follow-up, inbox triage, lead research or back-office updates. Tasks with strict rules and structured input are often better as a plain AI automation. We tell you which one fits after we see the task.
Can an AI agent make mistakes, and how do you control that?
Yes, like any system that works with language. That is why we design the agent around control: a person approves important actions, the agent only gets the access its job needs, spend and steps are capped, and every action is logged. We also test it on past cases before launch and keep measuring afterwards.
Which systems can the agent work with?
Anything with an API or a standard connection: email and calendar, CRMs, ERPs and accounting tools, helpdesks, databases, Slack and Teams, and your own applications. For systems without an API we look for another safe route before we promise anything.
How much does AI agent development cost?
It depends on the number of tools the agent uses, how complex the task is and how much autonomy it gets. We start with a small prototype, so you see results on your own data and a realistic estimate before you commit to the full project. Running costs (AI model usage) are measured per task and reported.
Which AI models do your agents use?
We choose per task: cloud models from OpenAI (GPT), Anthropic (Claude) or Google (Gemini), or open-source models that run on your own servers when the data is sensitive. The agent is built so the model can be swapped later without rebuilding it.
Have a task you want an AI agent to take over?
Tell us what you want to build. We reply with the next steps.
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