MarTech engineering capabilities
Social APIs, measurement models and data pipelines, and how AI has to fit them.
AI in a marketing product is only as good as the data it collects and the way each number is defined. These are the systems we have worked with and how the team works.
The team
Who builds it.
Product and metric design
Business analysts and designers who settle every metric screen by screen, in a prototype, before engineering begins.
AI engineering
Sentiment, emotion, toxicity and sarcasm models, ranking classifiers, language model enrichment and summaries, evaluated on your own data.
Data engineering
Platform collectors, crawlers, search indexes, streaming pipelines and master data with survivorship rules.
Platform engineering
Super admin portals, quota and cost tracking, white label options, roles per agency or dealership and documented APIs.
Systems
Systems we have worked with.
Built in client products. We scope yours in the Product Review.
| Area | Systems |
|---|---|
| Social platforms | Facebook Graph API, Instagram, X, TikTok, YouTube and LinkedIn, through official APIs and vetted data providers |
| Models | Pre-trained models for sentiment, emotion, toxicity and sarcasm, VADER, Word2vec and SVM classifiers, a larger language model for summaries |
| Search and crawling | Elasticsearch, Kibana dashboards, Scrapy crawlers |
| Streaming and stores | Kafka, Spark and Spark Streaming, MySQL, MongoDB, Neo4j |
| CRM and analytics | Salesforce read and write back, Fivetran ingestion, Azure SQL, Microsoft Fabric, Power BI |
| Ad tech | Self-serve campaign portals for streaming TV and digital billboards, with roles per dealership |
How the team works
One team across product, AI, data and platform.
A named lead engineer and US-hours overlap, from the first Product Review to production.
Every engagement
- We define every metric with you before we write code.
- We research each platform's API before we size the build.
- Every change goes through your pull request review and a separate QA environment.
- We work on your installed stack and versions, in accounts you grant and can revoke.
See it on your own platform.
Bring one product, metric or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per customer and what the platform APIs will allow.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.