Data Pipelines & Analytics
We build data pipelines that ingest, classify, and analyze at scale. LLM-assisted classification, vector-based similarity search, structured analytics, and dashboards your team actually uses.
01Overview
Enterprise data pipelines no longer need to be hand-coded ETL jobs. We build hybrid pipelines that combine traditional data engineering with LLM-assisted classification, semantic search, and AI-generated insights.
02Why choose this service
01
LLMs classify, categorize, and score records that rule-based systems miss.
02
Vector embeddings so your data is queryable by meaning, not just exact match.
03
Dashboards, scheduled reports, and PDF/Excel exports integrated with your existing BI tools.
04
Async processing, queues, and cloud-native architecture that grows from 10k to 10M records without rewrites.
03How we work
01
Where does data live, what formats, and what outputs does the team need?
02
ETL design, storage, classification strategy, and reporting surfaces.
03
Ship the pipeline. Test on your real data. Measure classification accuracy.
04
Reports, scheduled runs, alerts, and downstream integrations.
04Applications
05Technologies
06FAQ
Both. Rules handle the deterministic part, LLMs handle fuzzy classification and edge cases.
Async workers, queues, checkpointing, and incremental processing. We've shipped pipelines for millions of records.
07Explore more
End-to-end web applications built with modern stacks. From MVPs to scaled production platforms, shipped by a single team.
Cross-platform iOS and Android apps built with React Native. Native modules when needed, shared code where it makes sense.
Salesforce, HubSpot, and bespoke CRM setups with AI-enriched workflows, lead scoring, and deep integrations into your product and tooling.
Trusted in production by