// Services

Four practices.
One outcome: production AI.

Every engagement is delivered by senior engineers — no junior bait-and-switch. We work in 4 to 12-week sprints, with weekly demos and clear eval gates between phases.

Practice / 01

AI / ML Consulting & Strategy

We embed with your data leadership for 4-12 weeks to translate ambition into a roadmap with measurable ROI. From AI readiness audits to build-vs-buy frameworks to MLOps maturity assessments.

  • AI Readiness & Capability Audit
  • Use-case prioritization & business case modeling
  • MLOps & data platform maturity assessment
  • Build-vs-buy & vendor evaluation
  • Hiring and team enablement plans
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AI / ML Consulting & Strategy
01 / 04AI
Practice / 02

Custom ML Model Development

Production-grade models — not notebooks. Computer Vision, NLP, predictive analytics and recommendations, with eval suites and monitoring built in.

  • Computer Vision: defect, OCR, video, edge
  • NLP: classification, NER, semantic search
  • Forecasting & demand planning
  • Churn, propensity & fraud detection
  • Recommender systems & ranking
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Custom ML Model Development
02 / 04Custom
Practice / 03

Data Engineering & Analytics

The substrate AI runs on. Modern data stacks on Snowflake, Databricks, BigQuery — plus governance, lineage and self-serve BI dashboards that executives actually open.

  • Lakehouse architecture & migrations
  • dbt, Airflow, Dagster orchestration
  • Real-time streaming (Kafka, Kinesis)
  • Data governance, lineage, catalog
  • Looker / Tableau / PowerBI dashboards
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Data Engineering & Analytics
03 / 04Data
Practice / 04

Generative AI & LLM Integration

We build retrieval-augmented systems, internal copilots and customer-facing agents on Claude, GPT-5, Gemini and open weights. With evals, guardrails and observability — not vibes.

  • RAG over proprietary documents
  • Agentic workflows & tool use
  • Customer-support & sales copilots
  • Model selection & cost optimization
  • Eval harnesses, guardrails, red-teaming
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Generative AI & LLM Integration
04 / 04Generative

// How we work

A repeatable, audit-ready delivery process.

01
Discover

1-2 weeks. Workshops, data audit, success metrics.

02
Design

2-3 weeks. Architecture, model selection, eval plan.

03
Build

4-12 weeks. Iterative builds, weekly demos, eval gates.

04
Deploy

1-3 weeks. CI/CD, monitoring, rollout, handover.

05
Operate

Ongoing. Drift detection, retraining, SRE on-call.

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