Data analytics & data engineering consulting
Data analytics services, scoped to a fixed price and built in your own stack.
We build the pipelines, models, and reporting your team needs, in your warehouse and your repositories. Senior US data leaders design the work and stay on it. You own everything we ship, and your team can run it without us.
5 years
Building analytics that runs in production
10+ years
Minimum experience, every consultant on your project
What you get either way
- One problem named, scoped, and priced in writing
- A fixed price, not an hourly estimate that drifts
- A senior lead on the call, not a sales development rep
- The plan is yours whether or not you hire us
The analytics vendor behind the #1 dental analytics product in the US. We thrive in compliant environments.
Trusted by pre-revenue startups, $50M scale-ups, $200M hyperscalers, and $2B revenue industry leaders.
Our consultants built data infrastructure at unicorns, including BambooHR and Vercel.
Recommended by the CFOs who approve us and the ICs who inherit our work.
What we commit to before the work starts
Three things, agreed in writing, before you spend anything.
Trust the numbers in your board deck
Definitions your finance team agrees with, one metric meaning one thing across the company, and breakage that surfaces before a stakeholder finds it.
See what that involvesKnow the cost before you commit
Scoped, fixed-price projects. You see the number and the deliverable together, so you are never buying consulting by the pound or watching an hourly estimate drift.
Get a scope and a priceKeep running it after we leave
Everything lives in your warehouse, your repos, and your cloud account. There is nothing to license, and documentation and handover are deliverables, so your team can change it without calling us.
See how we hand overWhat we build
Three parts of the same job. Most engagements involve more than one.
Analytics and business intelligence
Getting from data that exists to decisions people make.
- Dashboards and reporting people actually open, built on definitions finance agrees with
- Metric layers and semantic models, so one number means one thing across the company
- Self-serve analytics that survives contact with non-analysts
- Analytics for a product you sell, embedded in your own application
Data engineering
The plumbing underneath, built so it does not need a specialist to survive.
- Data pipelines and ingestion from the sources you actually run, not the reference architecture
- Warehouse and lakehouse builds, plus the modelling layer on top
- dbt projects: staging, intermediate, and mart layers with tests and lineage you can read
- Migrations off the spreadsheet, the legacy warehouse, or the pipeline nobody will touch
- Data quality, monitoring, and alerting, so breakage surfaces before a stakeholder finds it
AI and MCP
The part after the demo, where it has to actually run.
- AI features that reach production: running in your cloud, behind your identity provider, with secrets out of the notebook
- MCP servers that give assistants governed access to your systems, with real authentication and an audit trail
- Predictive models for forecasting, churn, and propensity, trained on your warehouse rather than a stale extract
- Retrieval over your own documents and data, respecting the permissions your business already enforces
- The unglamorous half: monitoring, evals, retries, and cost controls, so it does not quietly break
The platforms we work in
We build in the tools you have chosen. If you have not chosen yet, we will tell you what we would pick and why, including when the answer is something cheaper.
Snowflake
Warehouse builds, modelling, cost and performance work.
Databricks
Lakehouse architecture, Delta pipelines, Unity Catalog governance.
dbt
Project structure, testing, documentation, and CI that holds up.
Tableau, Power BI, Looker, Omni
Semantic layers and reporting people trust.
Fivetran, Airflow, and friends
Ingestion and orchestration wired to your sources.
AWS, GCP, Azure
Built in your own cloud account, under your own controls.
MCP servers
Governed tool and data access for assistants, with auth and audit.
OpenAI, Anthropic, Bedrock
Model access wired into your stack, with evals and cost controls.
Salesforce, HubSpot
The CRM data most reporting arguments start in.
How we work with you
Four steps. You can stop after the second one with something useful in hand.
Step 01
We look at what you have
A short working session with the senior lead who would run the engagement. We walk your sources, your stack, and the reporting arguments you keep having.
Step 02
You get a scope and a price
One specific problem, named, scoped, and priced. In writing. If the price does not make sense next to the decision it unblocks, do not pay it.
Step 03
We build it in your stack
In your repos and your tools, with the same engineers every week. You can read every commit as it lands.
Step 04
We hand it over
Documentation, a walkthrough, and the keys. Your team owns the work and can change it without calling us.
What the people who hired us say
Finance and operations leaders who signed the invoices. All verified.
Aaron and the Aptologics team that he has assembled have completely transformed our business. They take a strategic view and help us to understand our business at a high level and be able to root cause the biggest opportunities and challenges. Aptologics continues to deliver results that are far beyond my highest expectations.
Aptologics' services have significantly streamlined our financial reporting and our operational reporting, providing us with a comprehensive view into the health of our company. … I would highly recommend Aptologics to any CFO looking to optimize the reporting internally or externally.
We understood what metrics actually impact others, and what metrics we thought impacted others but have no bearing on the success of the customer. … Without Aptologics helping us get to that level of data, we would have never known those things.
It's a real multiplier for us. The ability to dive in, assess what's going on in the business, and understand where the opportunities for growth and the key profit centers are... that higher-level view was the biggest gap in our organization, and it's not something I anticipated or expected. The feedback so far has been universally positive.
Aptologics does a great job painting a vision of what simple actionable reporting should look like. Aptologics was instrumental in not just data infrastructure changes, but also board-facing reports that drive the business. Aaron stays organized and has a fantastic business sense in addition to his technical acumen.
Tell us what you are trying to get done
A few sentences is enough to start. A senior lead reads it and replies with either a scoping conversation or an honest note that this is not our problem to solve.
- No discovery-call gauntlet before you speak to someone senior
- The scoping session ends with a scope and a price, in writing
- If you should buy a tool instead of hiring us, we will say so
Would rather just talk?
Skip the form and put 30 minutes in the calendar. Same senior lead, no write-up needed first.
Pick a timeQuestions about data analytics services
The things people ask before the first call.
Projects are scoped and fixed-price. The scoping conversation is free and ends with a specific number for a specific deliverable, so you can compare it against the decision it unblocks before committing anything. Delivery is not billed hourly, so the number you approve is the number you pay.
Get a scope and a price before you commit anything
One problem, named and priced in writing. Yours to act on however you like.
