Samir Wagle
Project brief
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Freelance AI engineering · Nepal / remote

Find where AI pays. Build it so it lasts.

I’m Samir Wagle, a freelance AI engineer and AI automation engineer in Lalitpur, Nepal. Technical partner for founders building with AI: workflow diagnosis, RAG development, implementation, API-cost control, and production handover. Available for remote collaboration worldwide.

Start with audit
Workflow before modelCost before scaleTests before claimsHandover before dependency

Services

Choose the problem you need solved.

Scope, deliverables, working process, and evidence for each engagement.

01

AI systems and automation audit

Fixed-scope diagnosis before implementation. One focused week for one system; two weeks when workflows or integrations cross teams.

Request audit
  1. 01

    Opportunity map

    Manual work ranked by value, frequency, feasibility, and failure cost.

  2. 02

    Cost analysis

    Current API spend, waste patterns, model-routing options, and estimated operating cost.

  3. 03

    System design

    Proposed architecture, integration boundaries, data flow, permissions, and human approvals.

  4. 04

    Delivery plan

    Security and reliability risks, phased implementation, acceptance gates, and ownership plan.

02

Build highest-value path after audit.

Models stay bounded. Code owns contracts. Humans retain control where failure is expensive.

01

Production AI pipelines

Models · data · evaluation · operations

Turn a model experiment into an observable system with explicit quality, latency, cost, fallback, and ownership boundaries.

What I build
  • Data ingestion, model routing, and output validation
  • Evaluation sets and release gates
  • Caching, batching, fallback, and API-cost controls
  • Deployment, monitoring, incident paths, and handover
02

AI systems and automation

Agents · workflows · document intelligence

Model calls stay narrow. Deterministic code owns contracts, permissions, retries, and expensive actions. Every workflow shows where judgment ends and automation begins.

What I build
  • Document and PDF extraction with source checks
  • Agents connected to CRM, inbox, and operations
  • Human approval for costly or irreversible steps
  • Scheduled data, content, and reporting pipelines
03

RAG and knowledge systems

Retrieval · grounding · evaluation

RAG is search plus evidence discipline, not a vector database demo. I benchmark retrieval first, define answer boundaries, preserve citations, and test when the system should refuse.

What I build
  • Corpus ingestion, chunking, and provenance
  • Lexical, dense, and hybrid retrieval baselines
  • Grounded generation and citation paths
  • Evaluation sets, failure analysis, and monitoring
04

Language and speech AI

Low-resource NLP · ASR · TTS

When English-first models meet low-resource languages, missing data and weak evaluation become product risks. I build baselines, datasets, adaptations, and tests that expose those risks early.

What I build
  • Dataset design, annotation, and quality checks
  • Multilingual embedding and model comparison
  • ASR/TTS adaptation and serving experiments
  • Multimodal ablations and error analysis

03

Judgment you can inspect.

Sanitized where work is confidential. Exact where evidence is safe.

Qualified project brief

Tell me where work, cost, or reliability breaks down.

Share current workflow, system, API spend, deadline, and failure risk. I review every brief before offering a call.
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