Practitioners, not theorists.
Engineers and operators who have built data and AI systems in production at scale. We have seen the same story across organisations of every size: an appetite for AI, a pressure to ship, and a data landscape that is not ready. The ones that succeed do the foundational work first. Once that is in place, the AI layer follows fast.
The three-layer model
Data Mobilisation & Foundation
Unify all data, establish pipelines, quality, and observability. Nothing else works without this.
AI-Powered Insights & Intelligence
BI dashboards, natural-language analytics, automated insight, cross-domain intelligence.
Custom AI/SaaS Applications
RAG, knowledge systems, agentic workflows, LLM products built on trusted data.
AI Developer Velocity — equipping your engineering team to build, deploy, and operate AI-powered workflows faster than ever before.
Three disciplines. One team.
Pulkit Khera
The engineer who builds the foundation everything else depends on.
Expertise
- →Data pipeline architecture & implementation
- →SaaS data migration & consolidation
- →Data quality frameworks & observability
- →Feature stores & ML-ready infrastructure
- →AI-powered BI and insights layer
- →MCP development & agent tooling infrastructure
Background
MSc Computer Science (Machine Learning & Data Analytics), TU Munich. Published researcher in federated learning. 5+ years across the full data and AI stack — currently sole ML Engineer at Podimo, owning end-to-end ML infrastructure, model deployment, and inference systems serving recommendations to 1.3 million users. Previously: large-scale data pipelines at Deutsche Bank and ETL systems for enterprise analytics at ZS Associates. GCP Certified Professional Cloud Architect.
Saumya Goyal
The engineer who architects AI platforms that ship to production and stay there.
Expertise
- →AI platform architecture & LLMOps infrastructure
- →RAG systems, vector search & knowledge layer design
- →Agentic workflow design with LangGraph & Airflow
- →LLM evaluation, observability & reliability (LangFuse, Qdrant)
- →MLOps pipeline integration into existing production stacks
- →Conference speaker, workshop facilitator & ML educator
Background
MSc Informatics, TU Munich. 8+ years building and shipping AI and ML systems in production — from Fortune 500 infrastructure at Verizon to MLOps platform delivery at BSH Home Appliances. Regular conference speaker since 2022 at MLcon Berlin & Munich, PyData, and MLOps community meetups across Germany and internationally. Visiting lecturer in AI & Data Science at Macromedia University, Berlin.
Ayush Diwan
The operator who connects intelligence to execution at every layer of the business.
Expertise
- →Business transformation & operating model redesign
- →System & process re-engineering, gap diagnostics & org rewiring
- →AI strategy, adoption roadmaps & change management
- →Agentic workflow design & AI-powered operations infrastructure
- →GTM strategy, presales operations & revenue process buildout
- →Product management & customer journey mapping
Background
MBA in Strategy, Systems & Operations, IIM Lucknow. B.Tech in Computer Science, SRM Institute. CEO’s Office at SkillNet Solutions, driving AI adoption, transformation, operations and growth. Prior: Program Manager, Startup GTM at AWS. Founded SceneSet Online; co-founded CampSkil Solutions.
Based in Berlin, Germany. Working with companies across Europe and India.
How we work
Discovery call — free, 30 minutes
We listen first. No proposal before we understand the problem.
Honest recommendation
We tell you what you actually need — including if the data foundation must come first.
Fixed scope and price
Clear deliverables, timeline, and payment schedule. No surprises.
Contract and upfront payment
Plain-English contracts. All IP transfers to you on final payment.
Delivery with weekly updates
You always know where we are. Scope changes discussed before they happen.
Handover + 2-week support
Full documentation, knowledge transfer, and 2 weeks of async support.
What you can always expect.
- →We never subcontract without your knowledge and approval
- →All code, pipelines, models, agents, and deliverables are your IP — transferred on final payment
- →We sign NDAs before any technical conversation
- →We will tell you if you need something different from what you asked for
- →We will not propose an LLM or agent project if the underlying foundation is not ready
Ready to talk?
Start with a conversation