Consulting services
Services
Production-grade data and AI systems for teams that need reliability, not just demos.
Engineering teams and departments running batch-heavy reporting, large document knowledge bases, or manual data workflows that block AI adoption.
Available for freelance projects from Q3 2025.
Service offerings
What I offer
Structured review of existing data pipelines, storage, and documentation to identify gaps between current state and AI-ready infrastructure.
Best for
Teams that want to adopt RAG, embeddings, or AI automation but are unsure where their data infrastructure stands.
Format
Fixed-scope assessment
Problems this solves
- — Inconsistent metadata making document retrieval unreliable
- — Pipelines lacking the observability needed for an AI-readiness review
- — No clear picture of data quality or coverage gaps
Deliverables
- — Gap analysis report with prioritized findings
- — Architecture recommendations for AI readiness
- — Phased implementation roadmap
End-to-end implementation of a document extraction, chunking, embedding, and retrieval pipeline for enterprise knowledge bases.
Best for
Teams with large Confluence, SharePoint, or document repositories that need reliable AI-queryable knowledge bases.
Format
Fixed-scope implementation sprint
Problems this solves
- — Knowledge locked in documents that AI systems cannot reliably query
- — Ad-hoc extraction pipelines with inconsistent metadata and no source attribution
- — No repeatable, observable process for keeping the knowledge base current
Deliverables
- — Production-ready extraction and embedding pipeline
- — Vector store integration with metadata contracts
- — Operational runbook and monitoring setup
Replace manual data workflows and reporting cycles with automated, observable pipelines that integrate AI classification, summarization, or routing.
Best for
Teams with recurring manual data operations — Excel-based reporting, email-driven workflows, or scheduled data preparation tasks.
Format
Fixed-scope delivery sprint
Problems this solves
- — Manual steps that introduce errors and delay delivery
- — Reporting workflows requiring constant human intervention
- — No visibility into pipeline state or failure causes
Deliverables
- — Automated batch workflow replacing targeted manual steps
- — Observability and failure alerting
- — Documentation and handover package
Engagement model
How engagements work
01
Discovery
Short scoping exchange to understand the problem, constraints, and what success looks like. No commitment required.
02
Proposal
Written proposal with explicit scope, deliverables, timeline, and success criteria. What is and is not included is stated upfront.
03
Delivery
Implementation with regular check-ins. All design decisions are documented as they are made.
04
Handover
Production-ready deliverable with operational runbook, monitoring notes, and documented boundary conditions.
Interested in working together?
Services are in active preparation and will be available from Q3 2025.
If you have a project in mind, reach out early — early conversations
help shape a well-scoped proposal.