Aimprosoft is now Certified in the Claude Partner Network
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Aimprosoft is Certified in the Claude Partner Network. Our engineers hold Claude certifications, and we are using that foundation to help clients take AI from a promising pilot to software that runs in production.
We have worked with Claude, powered by Anthropic, across our AI consulting and engineering practice, from retrieval systems that answer questions over company knowledge to coding workflows that change how our own teams ship software. Certification gives clients an outside signal that the people working on their project have been trained and tested on the platform they are building with.
About the Claude Partner Network
The Claude Partner Network is how Anthropic works with the firms that put Claude into production for customers. The Services Track recognizes partners for building a certified delivery team, delivering Claude use cases for clients, and proving the work through public customer references. Partners advance through Certified, Select, Preferred, and Global Premier tiers.
You can read more at claude.com/partners.
What this means for our clients
For the companies we work with, certification changes three practical things:
- A team that knows the platform. The engineers on your project have completed Claude training and certification, so less of your budget goes into learning on the job.
- Fewer surprises on the way to production. Most AI pilots stall between demo and launch. We design for security, permissions, testing and monitoring from the first sprint rather than bolting them on later.
- Honest model choices. Certification in Claude does not make us a single-model shop. We recommend Claude where it is the strongest fit for the task, and tell you when another option makes more sense.
“Our clients rarely struggle to get an AI demo working. The hard part is getting it into production safely and keeping it reliable once real users arrive. Having our engineers certified on Claude means the team on each project already knows the platform, so we spend less time learning and more time on security, testing and the details that decide whether a solution actually ships.” — Nick Martynenko, Delivery Director at Aimprosoft and Claude Certified Architect
How we build with Claude
Claude Code in everyday engineering | Assistants and agents that work with your data | Proof before you scale |
| Our developers use Claude Code daily as part of our AI SDLC framework. It drafts, refactors, and explains code. People still own the guardrails: tests must pass, every change gets human review, and the tool has clear limits on what it is allowed to touch. | These connect to the documents, databases, and tools you already use. Answers link back to their sources. Anything consequential waits for a person to approve it, and access follows the permissions your organization already has. | Before you commit a real budget, we test the idea on a small set of your actual examples. Within a timeframe we agree on upfront, you’ll have a working prototype and a clear recommendation: go ahead, adjust, or stop. |
Production-ready versions of AI apps you already have | Oversight that continues after launch | Choosing the right model for each job |
| Many teams come to us with a prototype already built, often written with AI help. We get it ready for real users and real data by working on security, performance under load, logging, and test coverage. | We evaluate model behavior before go-live and keep measuring it afterward. When a decision carries weight, a person stays in the loop. Every important step leaves a record you can show auditors, regulators, or your own customers. | We use Claude where it performs best and other models where they fit better. Each choice is weighed against output quality, data privacy requirements, response speed and running cost, so the solution makes sense on both technical and business terms. |
What comes next
For us, certification is a starting point rather than a finish line. Over the coming months, we plan to certify more of our engineers, bring Claude into more client projects, and share what we learn along the way: what worked, what didn’t, and what it took to move each solution from pilot to production. If that last part sounds familiar, our recent article on why most enterprise AI pilots never reach production is a good place to start.
Talk to our team
Are you exploring Claude for your business, or do you have an AI pilot that hasn’t reached production? Book a consultation, and we’ll take a look.
FAQ
Common starting points include summarizing and comparing long documents, answering staff or customer questions from your knowledge base with links to the source, drafting replies, proposals, and quotes from structured data, routing incoming requests, and running multi-step tasks through agents that pause for sign-off. We usually start with one process where it’s easy to tell whether the output is any good.
No. Claude is central to how our teams build and to much of what we deliver, but we choose the model for each task based on quality, privacy, speed, and cost. If a different model fits better, we’ll say so.
Before we touch any of your data, we agree on data handling rules, the AI provider’s terms, and an NDA if you need one. Anonymized or synthetic data is often enough to get started.
Start with a small, low-risk step that produces real evidence. Depending on where you are, that could be an AI readiness assessment to find the right use case, a focused AI pilot tested on your own examples, or a review of an existing AI app to prepare it for production.
