FACTORYZE

AI & MACHINE LEARNING

From prototypes to production: RAG, agents, evaluation, MLOps, and safety.

Research-to-Delivery Capability

Research Team

Problem framing, literature scan, benchmarking
Data audits, feasibility studies, baselines
Prototype design and experiment planning

Prototyping

RAG/agent prototypes with eval harness
Golden sets, rubric scoring, regression suites
Stakeholder reviews and iteration loops

Engineering Handoff

MLOps pipelines, observability, SLOs
Golden sets, rubric scoring, regression suites
Stakeholder reviews and iteration loops

Strategy & Capabilities

Strategy

Use-case discovery, ROI framing, risk analysis
Systems thinking: data, model, application, feedback
Build vs buy: API LLMs, open-source, fine-tuning

Capabilities

LLMs, Retrieval-Augmented Generation (RAG), agents
Classification, extraction, summarization, generation
Evaluation frameworks and human - in-the-loop review

Outcomes

Reduced cycle times via copilots and automation
Improved answer quality through eval-driven iteration
Production reliability with observability and guardrails

Solution Architectures

RAG Application

Chunking + embeddings + vector DB
Query re-writing and context post-processing
Citations and guardrails

Evaluation & E2E

MLOps pipelines, observability, SLOs
Golden sets, rubric scoring, regression suites
Stakeholder reviews and iteration loops

Agentic Workflows

Tool-use (APIs/DB)
Plans, memory, retries
Supervisor/worker patterns

Tooling & Stack

Models

OpenAI, Anthropic, Llama, Mistral

Embeddings

OpenAI, Voyage, Instructor

Vector DBs

Pinecone, Weaviate, pgvector

Orchestration

LangChain, custom pipelines

Eval

Gorilla, Ragas, golden sets

Observability

OpenTelemetry, custom traces

Data Engineering

Pipelines & Stores

ETL/ELT PIPELINES, CLEANSING, PII HANDLING
FEATURE STORES AND DOCUMENT NORMALISATION
MLOPS & PRODUCTION DEPLOYMENT
SCHEMA DESIGN FOR RETRIEVAL AND GROUNDING

Indexing & Retrieval

ADAPTIVE CHUNKING AND METADATA STRATEGIES
HYBRID SEARCH (BM25 + EMBEDDING RERANK)
FRESHNESS, INVALIDATION, AND RE-INDEXING

MLOps & Operations

CI/CD for AI

Dataset versioning
Prompt/config management
Eval gates in pipelines

Observability

Tracing IO/latency
Cost & token tracking
Anomaly & drift

SLOs & Reliability

Quality error budgets
Fallbacks/degradation
Anomaly & drift

Safety & Governance

Policies & Guardrails

ETL/ELT PIPELINES, CLEANSING, PII HANDLING
FEATURE STORES AND DOCUMENT NORMALISATION
MLOPS & PRODUCTION DEPLOYMENT

Evaluation & QA

TASK-SPECIFIC METRICS, RUBRIC-BASED SCORING
GOLDEN SETS, HUMAN REVIEW, RED-TEAMING
REGRESSION SUITES PER RELEASE

Case Studies

Real results from real projects. Here are some examples of how we've helped clients achieve their goals.

Solution Architectures

1-2 WEEKS

Discovery Sprint

Use-case deep-dive
Data audit
Architecture & plan

4-8 WEEKS

Evaluation & E2E

Prototype
Eval harness
Stakeholder demo

ONGOING

Agentic Workflows

MLOps & SLOs
Observability
Safety & governance