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Singapore · Lab infrastructure as a service

Infrastructure
for labs that ship.

Alfa Delfa is an infrastructure as a service control plane for research and data labs: experimentation wiring, lab native observability, and shared substrate you do not have to rebuild per project.

Reproducible runs, sub millisecond critical paths where it counts, and lineage you can audit. Built for teams that treat every experiment as production.

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Platform

Three part dashboard,
one control plane.

The product surface is a lab first dashboard: audit and lineage, workspace boundaries, and an AI native console grounded in your own telemetry. Same stack underneath, partitioned per lab.

Auditing and provenance
Fine grained logging, lineage, and reproducible runs across jobs and notebooks. Lab level and project level audit trails so you can answer what changed, when, and why.
Lab and project workspaces
Each lab gets a workspace; projects nest underneath with shared core infra. Per lab UI, metrics, and permissions without forking the platform.
AI native console
Embedded agent over results, ablations, diagrams, and logs already in Alfa Delfa. Explains regressions, compares runs, proposes next experiments. No pasted screenshots required.

What we build

Lab grade
infrastructure.

We sell a serious infra substrate for research labs: ingestion, stream processing, curated analytics, and observability wired for experiments, not slide decks.

01
Data infrastructure for experiments
Lakehouse and OLAP wired for experiment metadata, artifacts, and results. Storage and compute paths that keep runs reproducible under load.
02
Analytics for research telemetry
dbt backed models and semantic layers tuned to lab metrics: run curves, eval suites, hardware counters, and cohort level KPIs that survive peer review.
03
Streams for experiment events
Kafka first pipelines with Flink on the hot path. Sub millisecond critical paths for the events that gate training, eval, or hardware feedback loops.
04
Observability before results break
Prometheus and Grafana plus traces where needed. Lab native observability that surfaces drift, stalls, and silent failures before they poison a paper or a launch.

Architecture

How Alfa Delfa fits into your stack.

Sources emit experiment events into Kafka. Flink processes streams with deterministic state. Iceberg and ClickHouse hold experiment metadata, metrics, and results at the right granularity. dbt materializes curated models for analysis and dashboards. Prometheus scrapes service and pipeline health; Grafana is the default lens. Core services that sit on the hot path run in Rust and Go under Kubernetes where latency and memory behavior matter.

High level Alfa Delfa data and experimentation infrastructure for labs.
10x
Faster than typical legacy stacks (design goal)
<1ms
Sub millisecond critical path latency
99.9%
Pipeline SLO target
SG
Headquartered in Singapore, SG

Technology stack

Shared substrate,
hard limits respected.

Apache Kafka Streaming
Apache Flink Processing
ClickHouse OLAP
dbt Transform
Apache Iceberg Lakehouse
Kubernetes Orchestration
Prometheus + Grafana Observability
Rust / Go Core Systems
$ ad pipeline status
→ Ingestion: RUNNING
→ Transformation: RUNNING
→ Serving layer: RUNNING
→ Events/sec: 4,812,039
→ P99 latency: 0.81ms
→ Pipeline SLO: within 99.9% target
$

Why this stack

The lineup is tuned for research labs that need reproducible experiments and low latency experiment telemetry on a shared substrate. Multiple labs run as partitions on the same control plane, similar in spirit to how Palantir orients a common platform under tenant boundaries, but aimed at scientific workloads, open table formats, and stream first telemetry instead of generic BI sprawl.

How we work

DELFA

Design for failure
Every system assumes components will fail. Retries, dead-letter queues, circuit breakers, baked in from the start.
Measure everything
If it isn't instrumented, it doesn't exist. End-to-end observability is non-negotiable in every engagement.
Ship and iterate
We run lean, deliver fast, and scale incrementally.

Singapore, SG

Asia-Pacific Headquarters

Industry
Data Infrastructure & Analytics
Team size
11-50 people

Origin: Nanyang Technological University, Singapore. Research led roots, vendor grade delivery. Name and marks are for attribution only.

Ready to build?

Put the control plane
on your lab's side.

If you run a lab or data team and need experiment infrastructure or streaming pipelines, reach out with a short note about your stack and constraints.

hello@alfa-delfa.com LinkedIn ↗

Alternate contact: alfa.delfa01@gmail.com