Founder & CEO, Luminik · Oslo, Norway

I turn expensive, repetitive work into products people pay for.

3x technical founder. Today I'm building Luminik, and Alfred in the open.

$6M+
In customer pipeline
0→$3.6M
ARR in 15 months
Technical founder
Prasad Subrahmanya
AI to production
Multi-agent systems
0→1 founder
Scroll to impact

Impact

Outcomes.

Aura · Bain & Company
$3.6M ARR, from zero in 15 months

Built a workforce-analytics platform used heavily in PE and growth-equity due diligence, as venture CTO, and took it from zero to $3.6M ARR in 15 months. I owned the data infrastructure it ran on, and moved the warehouse to Snowflake as the analytical load grew.

0→1Enterprise SaaSPE & growth equity
Luminik
$6M+ pipeline sourced for customers

Founded a multi-agent platform that connects B2B event spend to revenue. I closed the first contract at $48K before the product existed, by running the workflow with scripts, spreadsheets and decks.

Multi-agent$48K pre-productFounder & CEO
Luminik · live results
8% lead-to-opportunity at RSA 2026

From 43,000 registered attendees to 1,840 ICP matches and meetings booked on the floor. Lead-to-opportunity reached 8%, up from 1.3% the year before, roughly 6x.

$2.4M RSA pipeline$2.0M Money20/20
Pipeline sourced at
Money20/20RSA ConferenceBlack HatDreamforceGartner SummitSaaStr

Work

Where I've built and shipped.

Founder and operator across GTM tech, private equity, field service, and investment management.

Luminik

Founder & CEO

Oct 2024 to Present

Building a multi-agent platform that connects B2B event spend to measurable pipeline: attendee extraction, enrichment, ICP matching, outbound, CRM sync, and revenue attribution.

Next.jsReactPythonHatchetVector searchAWS

SnowOptix

Founder

Jan 2024 to Oct 2024

A Snowflake cost-optimization tool. It was used by one of the global top-3 consulting firms, and the conversations while building it surfaced the bigger problem that became Luminik.

SnowflakeData engineeringCost optimization

Aura · Bain & Company

Venture CTO

Nov 2022 to Dec 2023

Took a workforce-analytics SaaS platform, used heavily in PE and growth-equity due diligence, from concept to $3.6M ARR in 15 months. Owned product, architecture, and the engineering team, and built the data infrastructure: a medallion warehouse on Snowflake with a Cube.js semantic layer, plus Lightcast and BLS taxonomies for comparable workforce data.

Enterprise SaaSSnowflakeAWSPE & growth equityTeam leadership

Mainteny

Co-founder & CTO

Aug 2020 to Oct 2022

Field-service management SaaS for maintenance companies across Europe. Built and launched the MVP solo in 3 months, raised a $2.7M seed, and scaled the team to about 15 across five countries.

Spring BootKubernetes$2.7M seedCRM
Earlier
Quantumrock Engineering Manager BaFin-regulated algorithmic trading platform, Munich
Wirecard Senior Software Engineer PCI-DSS card processing at scale, Munich
CommerceIQ Software Engineer Retail price intelligence at 100M+ SKUs/day
BlueJeans (Verizon) Platform Engineer Video platform, recording v1.0, Bangalore
6x more of the room, from the same booth. 1.3% of RSA to 8%.

Approach

How I work.

A few principles I keep coming back to.

  1. Get close to the problem

    I work next to the people who have the problem, so the product comes from what they do day to day.

  2. Earn trust before production

    The real work is the cases that break: evals, a judge I have calibrated, and adversarial tests, so I know how a system behaves before customers see it.

  3. Stay hands-on

    I write the code, review it, and read what the system produces in the wild. This kind of work does not lead well from a distance.

System

Most of what I build is one loop: signals, agents, evals, durable runs, outcomes.

  1. Signals
  2. Agents
  3. Evals
  4. Durable runs
  5. Outcomes

Skills

What I build with.

AI-native, and the systems under it. Drawn from what I'm shipping at Luminik and Alfred.

Agentic systems

Multi-agent orchestration, autonomous agent fleets (Alfred), LangGraph, MCP, tool use and planning

RAG & memory

Vector DBs, embeddings, hybrid and semantic search, context engineering, agent memory

Evals & guardrails

LLM-as-judge, eval harnesses, benchmarking, red-teaming, adversarial tests, safety gates

LLMOps & reliability

Tracing (Langfuse), OpenTelemetry, cost and latency control, failure handling, durable execution

Applied ML & model work

RL and reward design, prompt and context engineering, fine-tuning, multi-model routing (Vertex, OpenAI, Anthropic)

Distributed systems

Microservices and SOA, event-driven and async services (asyncio, aiohttp), FastAPI, Django, Spring Boot + Kotlin, Kubernetes, Kafka

Full-stack & mobile

Next.js, React, TypeScript, React Native and Expo, Tauri, end to end from data model to UI

Cloud & data platform

AWS, Terraform, Snowflake, data pipelines and warehousing, Postgres, CI/CD

How I get AI into production with teams →

Contact

Let's talk.

If you're building something hard in AI, or hiring someone who has, I'd like to hear about it.