White-label analytics engineering

Catch data errors before clients see them.

Clearline is the invisible technical data bench for boutique digital agencies: pipelines, models, and pre-handoff QA under your brand. Fixed scope. Fixed price. Clients never know we exist.

No channel conflict. Clearline does not maintain a client book and does not pitch your clients. That is by delivery architecture, not just policy.

The cost of getting it wrong

The expensive error isn’t the crash. It’s the clean-looking one that reaches the client.

Manual QA has a ceiling. Schema drift, type coercions, and outliers buried in tens of thousands of rows sit above it. When bad data lands in a client inbox, you’re no longer managing a data problem. You’re managing a relationship problem.

2 to 4 hours rework

Per error that reaches a client, before the explanation email.

20+ hours / sprint

Manual QA across analysts who still get different results.

Billable capacity lost

Delivery hours stuck in checks instead of scoped client work.

3 to 6 months to hire

Plus six-figure fully loaded cost for lumpy overflow demand.

Is this a fit?

Built for a specific type of agency

Right fit

  • Boutique digital agency, roughly 2 to 20 people
  • Active client data or reporting work, no dedicated analytics engineer
  • Need white-labeled output clients will treat as yours
  • Prefer fixed scope and fixed price over open-ended hours
  • Pain is concrete: drift, dirty models, manual QA, or pipeline reliability

Not the right fit

  • Enterprise brands with internal data teams
  • Tagging-only GA4 / GTM factory work
  • Weekly-changing scope with no defined deliverable
  • Strategy ownership without execution

Services & pricing

Fixed numbers. White-label delivery.

Lead with the Audit. Expand into builds and scarce retainer capacity when the work proves out, not before.

QA Automation Pack available as a scoped add-on when audits surface repeatable checks.

auditStart here

Data Quality Audit

$1,500fixed

Fixed-price review of client data infrastructure, pipeline hygiene, and reporting reliability. White-labeled PDF your agency can hand to the client.

  • At least 3 actionable improvements, or full refund
  • Schema drift, null spikes, and trust gaps named in plain language
  • Natural front door into Build, QA Pack, or Retainer
Discuss Data Quality Audit
build

Pipeline / Model Build

~$4,500fixed scope

Rebuild or stand up client reporting pipelines, dbt models, dimensional schemas, and validation checks under your brand.

  • Production-grade SQL / Python / dbt delivery
  • Handoff SOPs, READMEs, and quality checklist
  • Re-scope in writing if the job materially changes
Discuss Pipeline / Model Build
retainer

Monthly Retainer

~$3,000/ month

Embedded analytics-engineering and data-QA capacity for overflow sprints, without a six-figure hire and a quarter of lag.

  • About 3 active slots while founder-led
  • Overflow modeling, QA, and reporting automation
  • Best after an Audit proves fit
Discuss Monthly Retainer

How it works

From call to delivery in days, not months

  1. 01

    15-minute capacity check

    You describe the engagement, source systems, deliverable, and timeline. No pitch theater. If there’s a fit, we scope it. If not, you’ll hear that directly.

  2. 02

    Fixed-scope proposal in 24 hours

    One written number: deliverable, timeline, price, and what is needed to start. No hourly fog. No surprise change orders unless you change scope.

  3. 03

    Delivery under your brand

    Files, PDFs, dashboards, and repos arrive with zero Clearline branding: naming, structure, and docs matched to your agency.

  4. 04

    Handoff your team can trust

    SOPs, READMEs, and a quality checklist so internal teams can review external work without deep data expertise.

Founder proof

Regulated production discipline, not a brokered junior bench.

Clearline is built on the founder's Bank of America technical expertise and public technical projects.

9

production Python models

Through investigation → deployment with 100% of regulatory review requirements met

96%

faster validation

Streamlit QA automation cut per-request checks from 45 minutes to 2

200+

change requests

Zero non-compliant production changes by enforcing QA standards

85%+

accuracy restored

Root-cause work on performance drift across production models

Jacobyne Tambe

Founder, Clearline Data Analytics

Technical Data Analyst, Bank of America

Delivery stack

Explore the tools used on client work. Core tools first; supporting capabilities when the engagement needs them.

SQL

Warehouse queries and production model logic

BigQuery and MySQL for reliable extracts, joins, and model logic that client reporting can defend.

When the engagement needs more

The guarantee

If the Data Quality Audit doesn’t deliver three actionable improvements, you pay nothing.

Full $1,500 refund, no process theater. The audit either pays for itself in clarity and a white-labeled PDF you can pass to your client, or it costs you nothing.

Common questions

What agency owners ask before booking

Will my clients find out you exist?

No. Every deliverable arrives without Clearline branding. Naming, folder structure, and documentation match your agency. Invisible execution is the product, not a footnote.

Will my internal team trust external work?

Each engagement ships with handoff SOPs, READMEs, and a quality checklist so reviewers can validate work without deep data expertise.

Why not hire an analytics engineer?

Hire when utilization is full-time and stable. Until then you’re choosing between months of recruiting lag and a fixed-scope audit you can start after one capacity check. Retainer capacity is intentionally scarce.

What does the capacity check involve?

Fifteen minutes. You share the engagement shape; I come prepared. If there’s a fit, you get a written fixed-scope proposal within 24 hours.

Do you replace our reporting SaaS or do GA4 tags?

No. Keep tools that save assembly time. Clearline is for modeling, pipelines, and pre-handoff QA, not a white-label dashboard skin or tagging factory.

How should I evaluate Clearline works?

Start with the work that already shipped under regulatory scrutiny: production models, QA automation, and public technical projects, all labeled as founder proof. Then use the $1,500 Data Quality Audit as a low-risk test. It is fixed price, white-labeled, and fully refundable if it does not deliver three actionable improvements.

Ready?

You don’t need to wait six months for a hire. You need the data work done now.

Fifteen minutes. Tell me about the engagement. I’ll come prepared and tell you if there’s a fit.

Retainer slots limited to 3 active clients while founder-led. Currently accepting introductory calls.