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Enterprise AI transformation · since 2014

We build the foundation enterprise AI runs on, and the agents that run on it.

QueryNow leads AI transformation for enterprises in the US and Europe, from strategy to agents in daily use, with teams in Texas and Munich.

The four QueryNow practices: AI strategy on top, AI agents running on the AI foundation, and managed AI operations around both.01 · AI STRATEGYRoadmap and operating model02 · AI AGENTSCompliancereviewKnowledgeassistantQuotedraftingServicedesk03 · AI FOUNDATIONDatapermissionedRetrievalcited sourcesPlatformAzure or AWSGovernanceand security04 · MANAGED AI OPERATIONS
  • 200+

    Production deployments on AI and the Microsoft platform

  • Microsoft

    Solutions Partner

  • Azure · AWS

    The platforms we build on

  • 2014

    Founded in Germany

Enterprises we have delivered for

  • Bayer
  • Takeda
  • Rockwell Automation
  • Burckhardt Compression
  • Tillotts Pharma
  • WS Audiology
  • Zeppelin
  • Generac

Industries

Industries we build for

Choose an industry to see where a first agent usually starts and who approves its work.

Pharma & Life Sciences

AI for Pharma & Life Sciences

We built an AI compliance scanner for marketing assets for a European pharmaceutical regulator, checked against national and EU health-claims regulations. 620+ assets scanned, 11 rules per scan, traffic-light verdicts with source citations.

Go to Pharma & Life Sciences

Point of view

Most AI programs stall inside IT, long before the model is the problem.

Our engagements start by clearing what slows the first agent down: access to the data, approvals and the security review. The second agent reuses all of it.

Read our insights

Published research

How we engage

Four ways to work with us

Advisory

Strategy, roadmap and readiness for an AI program.

Build

One scoped workflow at a time, with acceptance criteria agreed in writing before the build starts.

Run

Managed operations after launch, measured against those criteria.

Outcome-linked terms

Commercial terms can be tied to the acceptance criteria you sign.

Every engagement starts with one scoped workflow and a written definition of done. Commercial terms are set in the statement of work.

How we engage

Questions

Questions buyers ask

Anything else, ask us directly. Talk to our team

What does QueryNow do?

We lead AI transformation for enterprises in the US and Europe. We work out where AI pays off first, build the data and platform foundation that agents need on Azure or AWS, build the agents on top of it and run them after launch. Since 2014 we have delivered more than 200 production deployments on AI and the Microsoft platform.

Where does an engagement start?

With one scoped workflow and a written definition of done. We agree the deliverables and the acceptance criteria with you before the build starts, and we build against that document. Larger programs start the same way, one workflow at a time inside a roadmap we agree with you.

What if the agent does not meet the acceptance criteria?

We fix the agent until every criterion passes. The criteria are written before the build starts and run as tests against your own data, so you can see each result. Commercial terms can be tied to those same criteria.

We already have an IT team.

Good. Your IT team should be in the scoping call, because they will own the system with us after launch. We build in your environment and hand them the code, the deployment and the documentation. The acceptance criteria include their handover requirements.

What counts as one workflow?

A workflow is one repeatable process with a defined trigger. We agree what input it receives and what output it must produce. Examples: prior authorization submissions, three-way invoice matching, deposition summary drafting, carrier vetting, CoA generation. We define yours together on the scoping call and write it into the agreement, including the acceptance criteria you signed off on. If the scope drifts during the build, we either trim it back to the signed spec or scope the extra work as the next workflow.

Who decides whether the acceptance criteria pass?

You do, against checks written in plain language and signed before the build starts. They run as tests on your own data, so everyone can see the result.

Who runs the agents after launch?

We do, if you want us to. We run, monitor and improve your agents after launch, measured against the acceptance criteria you signed. Your team approves what the agents produce, and we update them when your rules or systems change.

How are commercial terms set?

In the statement of work for each engagement. They follow the scope of the workflow, the systems it touches and who runs it after launch, and they can be tied to the acceptance criteria you sign.

Planning an AI program?

Talk to the team that builds it and runs it after launch.

  • Built to SOC 2, HIPAA and GDPR standards
  • EU AI Act-aligned delivery
  • Microsoft Solutions Partner