Forward-deployed AI engineering for production workflows.
We build the AI systems your business runs on, and stay until they work in production.
AgentsRAGPipelinesAutomationsEvalsObservability
The Active Sandbox Console
Select a workflow segment below to trace real-time pipeline execution, telemetry indicators, and node topologies.
From workflow to production
Every engagement starts with a business workflow. We decide what it actually needs: sometimes an AI system, sometimes plain software. Then we ship the smallest demo to prove the idea before delivering the production system that runs it.
Start with the business workflow
Understand the real work first: who does it, what flows in, which tools are already involved, where the decisions and exceptions live, and why the business wants it improved.
Most scoping calls end with less AI than the client came in asking for.
Choose the right system
Pick the system the workflow actually needs. That might be an agent, an automation, a RAG system, a data pipeline, an integration, a product feature, a dashboard, or software with no AI in it at all.
Sometimes the right system is a cron job and a spreadsheet. We say so.
Ship the smallest demo
Build the smallest version that does real work on real inputs, so the risks show up now instead of in production.
If the demo kills the idea, that's a cheap save.
Deliver the production system
Turn the demo into a deployed system: tested, documented, wired into CI and the client's existing tools, and built so it can grow when the workflow does.
Tests, CI, docs, handover. The unglamorous parts are the deliverable.
What we build
Past and ongoing engagements
What clients say
“Kartik is a very high-level ML engineer, able to solve wide range of tasks (NLP, OCR, using external APIs, self-hosted modules), he can do everything. Very highly recommended!”
“Excellent development skills, flexible, and delivered the solution quickly. Thanks”
“Very good guy. Good job. I paid bonus too on milestone 3”
Workflow Feasibility Scanner
Assess whether your operational workflow is a fit for AI engineering, traditional automation, or a hybrid approach — grounded in real deployment benchmarks.
What does the data in this workflow look like?
For enquiries, contact sales@merakinist.com
We typically reply within a day.