SERVICE 01 — LLM, HIGH-PRECISION RAG & GUARDRAILS
Artificial Intelligence & RAG Systems
Production-grade LLM architectures built for enterprise reliability: dense/sparse hybrid retrieval, semantic reranking, continuous evaluation, and security guardrails for dependable corporate decision-making.
Measured in production on a corpus of 40M+ heterogeneous documents (PDFs, SQL databases, OCR scans).
Continuous business benchmark score (Ragas & TruLens) validated through domain expert review.
From raw unstructured data to a deployed prototype validated by your business teams.
What your teams experience today
Faced with rapid technological shifts, most enterprise organizations encounter structural bottlenecks that stall industrialization and create operational friction.
Demo POCs that never scale to production
Attractive sandbox prototypes that collapse when faced with real volume, latency constraints, and enterprise security requirements.
Hallucinations and loss of stakeholder trust
Models generating plausible but false answers across critical contracts, internal policies, or operational documentation.
Technical debt and unmonitored model drift
Pipelines deployed without observability or drift metrics, where inference costs surge without verifiable ROI.
Compliance risks and sensitive data leaks (PII)
Lack of PII filtering and strict guardrails exposing your organisation to GDPR breaches and prompt injection attacks.
Four concrete deliverables, zero black box
Architecture Audit & Data Mapping
Exhaustive analysis of your document corpus, prioritization of high-value use cases, and business ROI evaluation matrix.
Hybrid RAG Pipeline & Ingestion Engine
High-performance chunking, multi-modal embedding, dense/sparse vector index (Qdrant/Pinecone), and cross-encoder reranking.
Security Guardrails & PII Anonymization
Real-time sanitization of personal data (PII), prompt injection shields, and factual verification before LLM response generation.
Continuous Evaluation & Synthetic Benchmark
Automated test suites (faithfulness, answer relevance, context recall) running on CI/CD to prevent regressions.
Four phases, verifiable milestones
Audit & Framing
Corpus analysis, definition of success metrics, and selection of models and vector infrastructure.
Prototyping & Hybrid Indexing
Deployment of vector index, chunking optimization, and initial retrieval experiments.
Guardrails & Integration
Integration of security filters, enterprise APIs, and user interface connection.
Production & Monitoring
Progressive deployment, token cost optimization, and real-time observability setup.
Engineered for high-stakes industries
Financial Analysis & Compliance Assistant
Instant analysis of thousands of annual reports (10-K, ESG, audit notes) with deterministic citation of sources.
Clinical Protocol & Research Query Engine
Semantic query engine across thousands of medical studies and clinical trial registries with zero hallucinations.
Automated Policy Comparison & Claims Review
Automated clause matching across multi-party insurance contracts and regulatory compliance checking.
A production-grade stack, not a prototype sandbox
LLM & ORCHESTRATION
VECTOR DATABASES
EMBEDDINGS & RERANKERS
EVALUATION & OBSERVABILITY
“Analyticatech’s RAG architecture enabled us to index 15 years of technical documentation with zero hallucination. Our support engineers save over 12 hours every week.”
What executives ask before getting started
Ready to deploy this capability across your organization?
Schedule a 30-minute scoping call with a senior architect to qualify your requirements, benchmark ROI, and receive a sequenced roadmap within 72 hours.