>_ Boutique Data and Technology Advisory

Thoughtful automation

so your team can work on higher-order priorities

Artificial intelligence offers infinite possibilities. We help you select, develop and deploy the few that matter.

// Sentiment Analysis — Building a report using NLTK and Altair |All Perspectives

>_ Trusted By

>_ Process

How we work

>_ 01

Diagnose

The gap between how your business is supposed to operate and how it actually does.

We map the gap between how your business is supposed to run and how it actually does — starting with how you make money, then tracing how work moves between people and systems. We’re looking for the buried processes, the spreadsheets standing in for databases, and the workarounds nobody questions anymore.

>_ 02

Redesign

Rework the process before introducing the technology.

Once we understand how things actually flow, we isolate a domain and rethink it cleanly. Sometimes that means consolidating tools. Sometimes deprecating third-party SaaS that’s become more habit than necessity. Sometimes narrowing scope to something smaller and more durable than what was originally envisioned.

We map the integration points — where data comes from, where it needs to go, which external systems need to talk to each other — and work through the less glamorous questions: schema implications, permissioning, and how much behavioural change this will actually demand from the people involved.

>_ 03

Prototype

Working software within the first week.

We move quickly to a live development environment — future users interact with the tool while it’s being shaped, not after. Data models evolve under real pressure. Schemas get adjusted when needed, often the same day. Interfaces are refined against how people actually use the thing, not how we assumed they would.

Cheap, fast iteration means less time debating what users might need and more time watching what they actually do with the thing.

>_ 04

Engineer

Stability, permissions, environments.

As the product stabilises under real usage, we formalise it. Clean database design. Role-based access control so the right people see the right things. Admin layers. Logging and audit trails — who did what, when, and whether it was approved.

We set up structured dev, staging, and production environments, and we’re comfortable operating across the full stack — application layer, infrastructure, CI/CD — tightening constraints as the system matures and more depends on it.

>_ 05

Harden & Transfer

Production-grade, then responsibly handed over.

Before release, we run structured security testing — penetration testing, automated security checks built into the CI/CD pipeline. We operate the platform initially to make sure it holds up under real load and real users.

Over time, ownership transfers to your team. We work inside your repository and environments with standard contributor access.

The goal is a system your team understands, can run, and can extend without us.

>_ 01

Diagnose

The gap between how your business is supposed to operate and how it actually does.

>_ Capabilities

What we build

Data

>_ 01

Frontier Data Tooling

Data systems (re)structured so models and agents can work reliably with them.

Data architecture: Enhanced ingestion tooling, refined pipeline orchestration and semantic layer clarity to make data more usable.

Agentic infrastructure: Queryable data surfaces that let agents retrieve context, reason across systems, and trigger tools safely.

Machine learning models: Forecasting, classification, anomaly, and other optimisation models trained on relevant operational data.

Operations

>_ 02

Custom Internal Software

Tailored operational tools designed for your workflows that standard SaaS cannot support.

CRUD applications: Purpose-built workflow systems with associated notification, RBAC and approval engines.

Human-in-loop review systems: Smart triage tools for automation vs human review for when judgment matters.

Workflow automation: Trigger-based workflows and mailbox re-routing to deprecate email-based processes with confidence.

Product

>_ 03

Product Innovation

Build the right thing through ongoing validation.

Prototype scaling: Take functional MVPs to market, able to take payments, monitor engagements and predict churn.

Customer validation: Tools to tighten discovery and validation loops for enterprise demand, persona matches, and pricing models.

Product-refresh: Workshop-based engagement to transition to a high-velocity process that aligns engineering with product.

>_ Why Us

What sets us apart

>_ 01

Established Track Record

A decade at the seam between product, engineering, and operations.

We’ve spent our careers in the gap between what’s required and what actually gets built — translating intent into working systems where the data is messy, processes are entrenched, and behavioural change is hard.

We’ve delivered zero-to-one applications at scale: internal platforms, a national PPE marketplace built under COVID pressure, and AI products utilising real-time behavioural data.

We’ve also been on the adopter side, and seen first-hand how systems fail when the problem isn’t understood well enough before the building starts.

Review our Portfolio

>_ 02

User-Centric Thinking

Most systems look strange from the outside, but they usually evolved for a reason.

We start with the workflow as it actually exists — the tangle of SaaS subscriptions, manual reconciliation, and tribal knowledge that keeps things moving.

Our experience predates the current AI wave. That meant years spent cleaning data, unpicking assumptions, and watching how people actually use systems. Over time tools accumulate, workarounds become permanent, and teams start optimising for metrics that no longer serve the original outcome.

Let's Talk

>_ 03

Data Fluent & Financially Literate

Well-developed systems require widespread user adoption to make economic sense. Many development teams discover this far too late.

In our leadership team, we came to technology through different routes — computer science and product on one side, finance and data engineering on the other.

That combination has given us cross-domain experience to deeply understand the cost-benefit of buy-vs-build decisions: whether the data exists, what shape it’s in, whether the numbers justify it, and whether people will actually change how they work.

Let's Talk

>_ 01

Established Track Record

A decade at the seam between product, engineering, and operations.

We’ve delivered zero-to-one applications at scale: internal platforms, a national PPE marketplace built under COVID pressure, and AI products utilising real-time behavioural data.

We’ve also been on the adopter side, and seen first-hand how systems fail when the problem isn’t understood well enough before the building starts.

Review our Portfolio

>_ About Our Founders

Founder-led by experienced operators

James Reid

0->1 operational product experience building Iceberg, an integrated contract, vendor and billing management platform

Operations and data engineering lead at a Singaporean insurtech during hyper-growth period

CFA, MBA, 4+ years M&A advisory at Rand Merchant Bank

John Reid

0→1 AI infrastructure product (Signals by Snowplow.io) conception, development & delivery

10+ years of product & data expertise @ VC-backed startups & scale-ups in Southeast Asia and Europe

Launched four 6-figure ARR products (Enterprise). Defined & implemented growth strategies for luxury e-hailing business in 4 markets across a 100m+ GMV business (Consumer)

>_ Let's Talk

Keen to connect?

Whether it's a process that isn't working, a data problem you've been sitting on, or a technology idea you're keen to explore — we'd like to hear about it.

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