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Sayfitech
Data & analytics

Custom analytics systems

Collection, warehouse, modelling and access designed around your specific questions.

Engagement
Phased build with your engineering team
Typical timeline
10–14 weeks
Starts with
A review of your current event names and the three questions you cannot answer today.
01The situation

Your product emits forty million events a month. The tool measuring them samples the data, caps history at fourteen months and prices by the seat, and the questions you most need answered are precisely the ones it was never designed to hold.

Why it matters

Analytics you own rather than rent from a vendor roadmap.

One number everyone trusts.

What we build

Concrete artefacts, handed over and documented.

01

First-party event collection you own, served from your own domain, unaffected by ad blockers and browser restrictions

02

A warehouse schema shaped around your product’s real objects instead of a vendor’s idea of a session

03

Ingestion with schema validation, so a field renamed in a release is caught before it corrupts a month of history

04

Backfill and replay, so a definition can change without throwing away the past

05

A query layer that both your analysts and your application can read from

06

Retention and residency rules enforced in the pipeline rather than promised in a contract

What changes

01

Questions the previous tool could not answer become ordinary queries

02

Event data stays inside infrastructure you control and can point an auditor at

03

Per-seat and per-event pricing stops setting the ceiling on curiosity

How it runs

Weeks 1–3

01Event design

We name the events and properties properly once, which is the decision the whole system lives or dies on.

Weeks 4–10

02Pipeline and warehouse

Collection, validation, storage and the query layer, built alongside your engineers rather than handed to them.

Weeks 11–14

03Migration and parallel run

Old and new run side by side, every discrepancy explained in writing, then you switch.

06Typical stack

Chosen per project. Named here so you can see the shape of it.

  • ClickHouse
  • Kafka
  • dbt
  • Dagster
  • Segment
  • Postgres

Questions we get asked

Next step

Tell us the outcome, not the tooling.

Send us the situation you are in. We will tell you which discipline it belongs to, what we would do first and what it costs, including when the answer is to wait.

Start a projectOr email us directlyinfo@sayfi.ai