Every engagement starts with one scoped workflow.
QueryNow builds the foundation enterprise AI runs on, and the agents that run on it. Clients work with us in four ways. Each one starts with a workflow you choose and a definition of done you sign.
Four ways to work with us.
Most clients start with one model and add others as the program grows. The commercial terms for each are set in its statement of work.
Advisory
Strategy, roadmap and readiness for an AI program. We find where AI pays off first and rank the workflows worth building. Then we set the operating model and governance the program needs to scale.
Build
One scoped workflow at a time, with acceptance criteria agreed in writing before the build starts. We build in your own Microsoft 365, Azure or AWS environment, test against the criteria you signed and hand over the code and documentation.
Run
Managed operations after launch, measured against those criteria. We monitor the agents and retest them whenever a model or one of your rules changes. Each month we report what they handled and how accurate they were.
Outcome-linked terms
Commercial terms can be tied to the acceptance criteria you sign. Where a workflow has a result both sides can check, the statement of work can tie the commercial terms to that result.
From the first call to a workflow in daily use.
- 01
A conversation with our team
First callYou tell us about the program or the workflow you have in mind, the systems involved and who checks the work today.
- 02
One scoped workflow
ScopingWe agree which workflow comes first and what done looks like for it: the inputs, the outputs, the accuracy it must reach and where a person approves the result.
- 03
A written definition of done
Before the buildThe acceptance criteria go into the statement of work with the deliverables and the commercial terms. Nothing is built before both sides sign.
- 04
Build, then run or hand over
DeliveryWe build in your environment and test against the criteria you signed. Then we run the workflow for you, or your own team takes it over with the documentation.
What the client signs.
A statement of work for each engagement. It names the workflow, the deliverables, the acceptance criteria and the commercial terms. After signing, the criteria change only by written agreement of both sides.
For a build, each acceptance criterion is a check that passes or fails on your own data, in your environment. For a run engagement, the same criteria become the measure we report against every month.
Your IT team grants the access we work with and can remove it at any time. The agents, the code and the documentation stay in your accounts.
What the engagements cover.
AI Strategy and Transformation
Where AI pays off first, and the roadmap and operating model to scale it.
AI Agents
Agents that work inside your own systems, with a named person approving what they produce.
Open →AI Foundation
Data that agents can reach with the right permissions, the platform on Azure or AWS, and the security and governance around it.
Managed AI Operations
We run, monitor and improve your agents after launch.
Open →One team from strategy to agents in daily use.
QueryNow leads AI transformation for enterprises in the US and Europe, from strategy to agents in daily use. Since 2014 we have delivered more than 200 production deployments on AI and the Microsoft platform for companies including Bayer, Takeda, Rockwell Automation and Burckhardt Compression.
QueryNow was founded in Germany in 2014 and has been a Microsoft partner since 2015. Our teams in Texas and Munich build on Microsoft Azure and AWS.
Questions buyers ask.
How is an engagement priced?
Commercial terms are set in the statement of work for each engagement, after scoping. The cost follows the scope of the workflow, the systems it touches, the volume, the governance it needs and whether we run it after launch.
Can the commercial terms depend on results?
Yes, where the workflow has a result both sides can check. Commercial terms can be tied to the acceptance criteria you sign, and the statement of work sets out how.
Do we have to start with a build?
No. Some programs start with advisory work to choose the first workflows and set governance. Others start with one workflow the team already knows it wants built.
Where does the work run?
In your own Microsoft 365, Azure or AWS environment. The agents, the code and the documentation stay in your accounts whether or not we run them after launch.
Who approves what an agent produces?
A named person on your team. The acceptance criteria say where a person approves the output, and the agent works inside that rule.
Planning an AI program? Talk to the team that builds and runs it.
Every engagement starts with one scoped workflow and a written definition of done. Commercial terms are set in the statement of work.
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