AI agent development company for real business work
QueryNow is an AI agent development company based in Plano, Texas, with a team in Munich. We build custom AI agents for business that read your documents and hand each result to a person for approval. Each agent takes two weeks to build, and you pay $10,000 only after it passes the tests you signed.
Why most AI agents for business automation never reach production.
No clear approval point
The agent can draft a decision, but nobody decided who signs it off or what happens when they disagree.
Borrowed logins
The agent runs under someone's personal account with broad access, so security teams block it before launch.
A demo on clean data
It worked on ten tidy samples. Real volume brings scanned pages and missing fields.
Locked to one model
Prompts and business rules sit inside a vendor product, so each better model means starting over.
What are AI agents?
AI agents are software that take a task, work out the steps and use your systems to finish it. The agent reads an email, opens the attachment, checks the details against your records and prepares the next action. People call this agentic AI because the software works toward a goal over several steps.
A chatbot answers a question and waits for the next one. An agent keeps going until the task is done or it needs a person to decide. So approvals and access matter far more for agents than they ever did for chat tools.
Where a person stays in charge of the agent.
In our builds the next action is usually a draft. The agent fills in the certificate, matches the invoice, answers the SOP question or flags the clause, and a person on your team approves or corrects it. Over time you can let the agent finish routine cases on its own and send only the exceptions for review. You decide where that line sits, and you can move it.
Good AI agents for business operations are narrow. They do one job on real volume, with a clear owner. We start with one workflow and add the next once the first one is paying its way.
Examples of custom AI agents for business teams.
These are the kinds of agents we build. They are examples of the work, written to help you spot a fit, and each one gets scoped to your own systems and rules.
Document intake
Reads incoming forms and letters, pulls out the fields your team retypes today and files them in the right record for review.
Invoice matching
Matches invoice lines to purchase orders and receipts, and sends each mismatch to an approver in accounts payable with a note.
Certificates of insurance
Drafts a certificate from the policy data and the holder request, checks the wording against the contract and sends it to a CSR to approve.
SOP lookups
Answers procedure questions from your approved SOPs only, with a link to the exact section, and respects who may see which document.
Contract review
Compares an incoming contract with your standard positions, marks the clauses that differ and drafts suggested redlines for counsel.
Approval steps, identity and least privilege in every agent.
Every agent we build has an approval step designed in from the first day. We write down which outputs need a human and who that human is. We also agree what the agent does when the approver rejects its work. Each approval is logged with the person and the time, so you can show the record to an auditor or a customer.
Each agent also gets its own identity in your directory, such as a managed identity in Microsoft Entra ID or an IAM role in AWS. It holds the least access the task needs and nothing more. When the agent reads a document, it sees only what that identity is allowed to open, and every action it takes lands in an activity log your team controls.
We build systems to SOC 2, HIPAA and GDPR standards, and every implementation is aligned with the EU AI Act. That matters for our clients in pharma and financial services, and it makes security review faster for everyone else.
AI agent development services from Plano, Texas and Munich.
Our headquarters is in Plano, Texas, and our European team works from Munich. US clients get a team in their time zone, and European clients can keep data and delivery inside the EU. We have built production software for clients in both regions since 2014.
We automated radiology sales operations for Bayer. Other clients include Takeda, Rockwell Automation, Tillotts Pharma and Burckhardt Compression, and the same senior people who scope your agent are the ones who build it.
What you get with every agent.
Signed acceptance tests
The tests the agent must pass, agreed in writing on day one and run on your own data at the end of week two.
Human-in-the-loop by design
Named approvers for each output type, with a log of every approval and correction.
Its own identity
A dedicated identity with least-privilege access and a full activity log inside your tenant.
Connections to your systems
Integrations with email, SharePoint, your ERP or CRM and the line-of-business tools the workflow touches.
Evaluation sets
A test set built from your real cases, so you can rerun it when the model or the rules change.
Your code, your cloud
The agent runs in your own cloud account or Microsoft 365 tenant, with the code in your repository.
From workflow to working tool in two weeks.
Scope and sign
We define the workflow, the deliverables, and the acceptance criteria, and sign an agreement on them before anything starts.
Build
We build the tool in your environment, with Claude Code and automated evaluation against your own data.
Pay when it works
$10,000, due only after every criterion in the signed agreement is met. Nothing before that.
We scope one agent with you and sign the acceptance criteria on day one. We build it in your environment in two weeks, and you pay $10,000 only after every criterion is met. Nothing upfront. One agent at a time, and you can stop after any of them with a working system in hand.
See what AI implementation costs →
Tell us the workflow →Questions buyers ask.
What does an AI agent development company do?
It designs and builds software agents that carry out business tasks using your systems and data. Our work covers scoping the workflow, connecting the agent to your tools, setting up approvals and access, testing on real cases and handing it over to your team.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions in a conversation. An agent takes a task and works through it, reading documents and checking records before it prepares an action. In our builds a person approves the action before it takes effect.
How do you keep AI agents for business automation safe?
Each agent has its own identity with least-privilege access. Every important output goes to a named approver, and the agent logs each action it takes. The agent can only read what its identity is allowed to open, so it cannot surface documents a user could not see.
How long does AI agent development take?
Two weeks of build for one agent, after a short scoping step. The acceptance criteria are signed on day one, and we run them with your team at the end of week two.
How much do custom AI agents for business cost?
Each agent is $10,000, paid only after every acceptance criterion is met. Nothing is due upfront. Running costs for the model and cloud services sit in your own account, and we estimate them during scoping.
Should I hire an AI agent developer or a firm?
If you want to hire someone to build an AI agent for one internal task and you have an IT team to own it, a good freelance AI agent developer can work. A firm makes more sense when the agent touches customer data or regulated records, or needs approvals and security review. Our price is fixed at $10,000 per agent and paid only after it passes your tests, so trying a firm carries little risk.
Where is QueryNow based?
Our headquarters is in Plano, Texas, and our European team is in Munich. We work with companies across the US and Europe, and European clients can keep delivery and data in the EU.
Which models do you build AI agents on?
We build on models from Anthropic (Claude), OpenAI and Google, reached directly or through Azure OpenAI and Amazon Bedrock. We choose the model per workflow by running your test cases against the candidates. Prompts and business rules stay in your code, so you can move to a better model later.
How do you build AI agents for a business?
We start with one workflow and look at real samples of the work. On day one we sign the acceptance criteria, then build the agent in your environment over two weeks with its own identity and an approval step. At the end we run the tests with your team, and you pay only when they pass.
Ready to ship AI that actually works?
Send us the workflow. We return a fixed scope, price, and acceptance criteria in 48 hours. You pay $10,000 only after it works.
Tell us the workflow →The agentic enterprise, without the hype
Where agents earn their keep in an enterprise, and where they do not yet.
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