Managed
Data products
$2.5K–$8K / month
A focused team builds and runs a data product end to end. You get software, not a report.
- Discovery, design, build, deploy
- Hosting, monitoring, and on-call
- Ships every month
- Your data exportable at any time
Data & AI engineering studio · Houston, TX · working worldwide
Data and AI systems your business runs on.
We design, build, and run custom data products, ML pipelines, and grounded AI agents, on your infrastructure and under your ownership.
2,000+hours saved for clients yearly
99.9%uptime across client deployments
2 weeksfrom kickoff to first ship
Rows processed · 24h
48.2M
↗ 6.1% vs prior day
Pipeline SLA
99.94%
0 breaches this month
Forecast error
4.2%
↘ 0.8 pts after retrain
Throughputrows / hour · last 24h
Recent runs
ingest_wells_scada2m
dbt_core_marts9m
forecast_daily_v14running
agent_eval_suite41m
quality_contracts1h
Illustrative interface. Sample data, not a live client system.
Snowflake
Spark
Databricks
Postgres
Airflow
Docker
Grafana
BigQuery
Kubernetes
Kafka
Terraform
Prefect
01 · What we do
Six things, done properly.
Every engagement ends with software running in production, documented and supported.
i.
Custom software & portals
Internal tools, operations systems, and customer portals your team actually uses. Built as software, deployed to the environment the engagement runs in.
ii.
APIs & real-time integrations
Services that move data between platforms as it happens, instead of nightly exports and Monday-morning reconciliation.
iii.
OCR & document extraction
Models that read PDFs, scans, catalogs, and invoices and load the results straight into your systems. Nobody retypes anything.
iv.
ML pipelines & forecasting
Demand, time-series, and operational forecasts that ship, with backfills, monitoring, and drift handled.
v.
Grounded AI agents & RAG
Retrieval, evaluations, guardrails. Agents that touch your data with traceability, not chatbots that guess.
vi.
Embedded delivery
We sit in your standups, learn your vocabulary, and write code beside your team. Nothing thrown over a wall.
02 · How we work
Call to production in four steps.
Fixed scope, fixed price, and working software at the end of every stage.
Step 1
Discovery call
Thirty minutes, free. We map the problem, the data, and what success means.
Step 2
Pilot sprint
Two weeks, fixed price. Ends with software running on your real data.
Step 3
Production
Deployed with monitoring, documentation, and a runbook your team can follow.
Step 4
Operate
Monthly cycles. We run it, or your team takes the keys.
03 · Pricing
Two ways to engage.
No retainers for slideware. You pay for systems that run.
Embedded
Data/AI Consultant
$120–$150 / hour
A data/AI consultant inside your team: your repo, your priorities.
- Senior ML and data engineering
- Standups, code review, mentoring
- Flexible cadence, monthly minimum
- Volume discounts at 80+ hours
Every engagement starts with a free discovery call. Not sure which fits? Just ask.
What you get either way
Shipped software, not adviceDomain fluency before codeAI with evals and guardrailsYour data exportable, any timeProduct-grade craft, even for internal tools
04 · Security
Your data, handled carefully.
Where a system runs is agreed before the build starts: inside your environment, or a dedicated environment we manage for you. Either way, access is yours to grant and revoke.
Deployed where you need it
Your AWS, Azure, or GCP account, or a dedicated environment per client on infrastructure we run. Decided with you, before anything is built.
SSO, RBAC, least privilege
SAML or OIDC single sign-on, role-based access on every surface, and scoped service accounts by default.
Audit logs on every action
Reads, writes, model runs, and agent calls are logged with actor and timestamp, exportable to your SIEM.
Secrets and key management
No credentials in code. We use your secret manager, rotate on schedule, and scope keys per environment.
AI with guardrails
Grounded retrieval, refusal and safety evals, PII redaction, and no customer data sent to train third-party models.
Clear terms, agreed up front
What you keep, what is licensed to you, and what happens if we part ways, written into the agreement before the first line of code. NDAs are standard.
Infrastructure runs on providers holding SOC 2 Type II and ISO 27001, with a dedicated environment per client.
05 · FAQ
Common questions.
Who owns what?
Your data and the outputs the system produces are yours, and exportable at any time. The reusable platform we bring to every engagement stays ours and is licensed to you. Which parts are which is written into the agreement before work starts, so nobody is guessing later.
Do you work with our existing stack?
Yes. We build on what you already run: Postgres, Snowflake, dbt, Databricks, plain S3, and we don't rip out things that work.
How fast can we start?
Discovery call this week. The pilot sprint usually starts within two.
Do we need our own data team?
No. Some clients have none; others embed us inside a ten-person team. Both work.
Is our data safe?
Access is scoped to what the work needs and revoked when it ends. Where the system runs is agreed up front, and the environment is dedicated to you rather than shared. NDAs are standard from the first call.
Where are you based?
Houston, Texas. Remote-first, with clients worldwide.