AI agent development company for business

JEEKSSHIRE 24 is an AI agent development company that builds assistants which read your documents, emails and data, answer staff and customers, and carry out steps of the work inside your systems. We handle the full cycle: process review, connecting data sources, launch, an action log and ongoing support. Our experience is hands-on: the AI lawyer in our own product, Legal, works with real users every day.

Custom AI agent development: what we build

An agent pays off where people spend time searching, reading and copying information between systems. Every agent we build gets a defined job, access to the right data and a clear output.

• Knowledge-base assistant: answers staff questions from policies, manuals and contracts and shows which document the answer came from (RAG, meaning search by meaning across your own sources).
• AI chatbot for your website, Telegram and other channels: understands free-form questions, answers from your materials and hands difficult cases to a person.
• AI agent for customer support: sorts incoming requests, finds the answer, drafts a reply and opens a ticket when a specialist is needed.
• AI agent for sales: qualifies leads, fills in CRM records and reminds the team of the next step.
• Document agent: reads contracts, emails and scans, extracts data and flags risky terms.
• In-process agent: runs workflow steps such as creating a task, sending a notification or updating a record, within the permissions you grant.

If buttons and a fixed script are enough, we will suggest a simpler Telegram bot without AI.

Who needs an AI agent and which problems it solves

AI integration does not pay off everywhere. Good candidates are processes with repetitive text and rule-based decisions: incoming emails, customer questions, document checks, internal lookups.

• Support and service: the first line answers faster and people focus on complex cases.
• Sales: leads are not lost, and managers open a CRM record that is already sorted.
• Legal, accounting and procurement: the agent reads documents and highlights what a person should look at.
• Small businesses: an AI assistant covers routine work that has no dedicated employee.

For guidance on choosing the first task for an agent and setting realistic expectations, read our guide AI agent for business.

How we build and ship an AI agent

1. Task review. We find where time is lost and agree on what success means: which questions the agent closes alone and which go to a person.
2. Data and access boundaries. We define the sources, such as documents, email, CRM and knowledge base, and the agent's rights: what it may read and what it may change.
3. First version on your examples. We build the agent on real questions and documents and review the answers together with your team.
4. Integrations and guardrails. We connect your systems, add human approval for important actions, an action log and failure alerts.
5. Launch and growth. We release to a limited group, read the log, fix weak spots and widen the agent's scope.

If you do not have a written spec yet, start with our guide on writing software requirements, or simply describe the problem in your own words in the request form.

What you get from our AI agent development services

• A working agent in production, connected to your sources and channels.
• The source code and the rights to it.
• Documentation of how the agent works, which permissions it has and how to release it.
• An action log and configured failure alerts.
• A set of test examples that shows answer quality after every change.
• Ongoing support and development by agreement.

Our own AI product: the AI lawyer in JEEKSSHIRE 24 Legal

Legal is our own AI-powered document editor. It helps draft a contract from a description or review an existing one: find risky terms, vague wording and unclear deadlines. The AI lawyer answers questions about the document and opens the relevant section instead of retelling the text in its own words.

Legal works with PDF and DOCX and recognizes text from images right in the browser, so a document does not have to leave the user's computer. It runs on the web, Mac and Windows, and its interface is available in 184 languages, including right-to-left Arabic and Hebrew. We bring the same principles to client projects: the agent works with the document, not instead of it, and privacy is an engineering requirement.

AI agent vs chatbot vs workflow automation

These three are often confused, although they solve different problems.

The best result often comes from a combination: business process automation provides reliable mechanics, and the agent takes the part where text has to be understood.

AI integration services: CRM, email, knowledge bases, messengers

We connect the agent to the systems where your process lives:

• CRM and accounting systems: reading records, creating tasks, updating statuses;
• email and messengers, including Telegram: incoming requests and replies;
• file storage and knowledge bases: documents, policies, manuals;
• your website and customer portal: an AI chatbot right inside the interface.

We choose the language model for the task, weighing answer quality, speed, running cost and requirements on where data is processed.

Data security and control over agent actions

You set the access boundaries. The agent sees only the sources it has been given, and important actions, such as sending a message to a customer, changing a record or making a payment, go through human approval. Every action is written to a log, so you can see what the agent read, what it decided and what it did.

Secrets and keys are kept outside the code and the repository, and data does not travel where it has no business being. This is a requirement for every change, as in our own products.

How much does an AI agent cost and how long does it take

A first working version usually takes a few weeks: we connect sources, set access boundaries and test answers on your real examples, then expand. Timeline and cost depend on:

• the number and state of data sources, from a tidy knowledge base to scattered files;
• how many systems need to be connected and whether they have an API;
• which actions the agent performs on its own and which need approval;
• the required answer quality and the size of the test set;
• the channels: website, messengers, email, internal systems.

Running cost, meaning requests to the language model, is estimated separately. Read more about price factors in our guide on software development cost, and see all our services on the Software development page.