Data platform build
Ingestion through to warehouse and dashboards — one pipeline the whole company can trust.
Drawing 001 — System overview
We draw the architecture
before anyone writes code.
Divys designs, builds and operates the data pipelines, platforms, backends and AI systems behind products that cannot afford downtime. Every decision documented, dimensioned and justified — like any other piece of engineering.
Load balancer
CDN
Terminates TLS, absorbs bursts
API gateway
Auth service
Cache
Rate limiting + token validation at the edge of the mesh
Service A
Service B
Service C
Independently deployable, independently scalable
Database
Message queue
Object store
Durable, replayable, backed up and restore-tested
Streaming
Warehouse
Vector index
Model serving
Where the pipelines and the models live — evaluated, versioned, budgeted
500M+Requests handled
99.99%Uptime achieved
50+Systems built
<100msp99 latency
Sheet 02 — Capabilities
What we actually do.
Seven practices. Between them they cover the whole path from raw data to a system running in production — including the parts everyone is rebuilding for AI right now.
RefPracticeWhat that means
01
Data engineering
We build the pipelines. Batch and streaming ingestion, change data capture, lakehouse modelling and orchestration — data that lands on time, is replayable, and never silently drops records.
02
AI & LLM systems
Getting models out of notebooks and into production. Retrieval, inference serving, evaluation harnesses, agent orchestration and guardrails — with real latency and cost budgets attached.
03
Platform engineering & DevOps
Internal platforms, CI/CD, GitOps and infrastructure as code. Golden paths so product teams ship on their own instead of filing tickets and waiting on someone else.
04
Cloud architecture & FinOps
Migrations, multi-cloud design, and spend that grows slower than usage. We show you the bill before and after, line by line.
05
Backend & API engineering
Services that hold under load. Event-driven where it earns its keep, boring and predictable where it doesn't — whichever your team can actually operate at 3am.
06
Reliability & observability
SLOs that mean something, tracing that finds the cause, and an on-call rota that doesn't burn people out. Incident reviews that actually change the system.
07
Security & compliance
Zero-trust access, managed secrets, supply-chain scanning, and SOC 2 / ISO 27001 readiness — without freezing delivery for a quarter.
Tooling follows the problem, not the other way round. We're comfortable across the usual cloud, data and orchestration stacks — and we'll tell you when the boring option is the right one.
Sheet 03 — Assemblies
What we're usually hired to build.
Four engagements make up most of our work. Each begins with a drawing, not a ticket.
AI features in production
Retrieval, agents and inference shipped with evals, guardrails and a cost ceiling.
Platform modernisation
Kubernetes, CI/CD and IaC rebuilt so deploys are routine instead of an event.
Backend replatforming
Rebuilding services that have hit their ceiling, without a big-bang cutover.
Sheet 04 — Method
How an engagement runs.
Documented decisions, visible progress, no black boxes.
-
1
Week 1
Discovery & strategy
Deep dive into challenges, goals and constraints. The architecture is mapped before a line of code exists.
-
2
Week 2
Architecture design
Detailed system design with scalability, security and performance built in. Every decision documented and justified.
-
3
Weeks 3–12
Agile development
Sprint-based delivery with continuous integration, automated testing and regular deployments. Progress every day.
-
4
Week 13+
Launch & optimise
Production rollout with monitoring, alerting and tuning. We stay until the system is boring.
Sheet 05 — Tolerances
The numbers we want to be judged on.
Not a highlight reel — the tolerances we design to. We agree them with you before the work starts, you measure them, and we're happy to see them written into the contract.
Uptime, agreed as an SLO
99.9%+
Set before we start and measured from outside — your monitoring, not our dashboards.
p99 latency, budgeted up front
<100ms
Every service ships with a latency budget attached, not a hope.
Cloud spend, first quarter
−30%
A target set from your actual bill — and reported against line by line, hit or miss.
First response, always
2 hrs
You talk to the engineer who built it, not an account manager.
Miss one and we'll tell you before you notice it — that's the part most people skip.
Sheet 06 — Request for review
Rev. A
Let's look at your architecture together.
Bring a diagram, a cloud bill, or just a problem. Forty-five minutes with a senior engineer who will tell you where the risk is.
Tell us when suits you and we'll send back a calendar invite — no account, no forms to chase.