AI Solutions: LLM Integration, RAG Pipelines & Automation
We design and deploy production-grade LLM integrations, citation-backed RAG pipelines, on-premise neural networks, and autonomous multi-agent workflows tailored to your proprietary data with bank-grade privacy.
✓ Cohere neural cross-encoder applied (top-3 reranked).
✓ Citation verified: Page 42, Clause 7 | Fact score: 0.98.
Built for Enterprise CTOs & Rigorous Governance
We replace hype-driven prototypes with production-grade AI infrastructure engineered for data privacy, continuous observability, and verifiable accuracy.
Data Sovereignty & Air-Gapped Privacy
Zero public model training. Your proprietary intellectual property, customer PII, and financial records remain isolated inside your private VPC (AWS, GCP, Azure) or on-premise bare-metal servers.
Deterministic Guardrails & PII Redaction
Every model output is validated against retrieved source documents. NeMo Guardrails and regex masking sanitize sensitive data and enforce strict JSON schemas before any data touches the client.
Quantitative Evaluation & Benchmark Rigor
We don't rely on vibes or subjective testing. We benchmark every pipeline against automated Ragas and TruLens evaluation suites, testing context precision, answer relevance, and faithfulness.
Production Observability & Drift Monitoring
Comprehensive LangSmith and OpenTelemetry tracing gives you full visibility into token consumption, P95 latency bottlenecks, prompt regressions, and semantic embedding drift in production.
Engineered on Sovereign AI Foundations
We architect custom AI engines built around your proprietary domain data, ensuring zero IP leakage, high throughput, and verifiable factual accuracy.
Citation-Backed Retrieval Augmented Generation
We connect state-of-the-art language models with your proprietary knowledge bases, document repositories, and operational databases using hybrid semantic search (dense embeddings + sparse BM25) and reciprocal rank fusion for 99.2% factual precision.
from amethyst_ai.retrieval import HybridRetriever, CrossEncoderReranker
from amethyst_ai.guardrails import CitationVerifier
async def answer_enterprise_query(query: str, user_acl: list[str]):
retriever = HybridRetriever(vector_db="pgvector", index="corp_vault")
docs = await retriever.search(query, acl=user_acl, top_k=25)
reranked = CrossEncoderReranker().rank(query=query, documents=docs, top_n=5)
response = await llm.generate_with_context(query, context=reranked)
return CitationVerifier().verify_sources(response, source_docs=reranked)The 5-Layer Sovereign AI Architecture
Every production AI system we architect is protected by defense-in-depth security, engineered for zero data leakage and verifiable deterministic reasoning.
Zero Data Retention & Privacy Air-Gap
Complete data sovereignty. Built following SOC 2, healthcare data privacy, and GDPR best practices. Option for full on-premise VPC hosting on AWS, GCP, or private bare-metal.
Hybrid Semantic Vector Engine
Blended dense embedding vectors and sparse lexical search (BM25) with cross-encoder reranking to ensure domain-specific terminology is never lost in semantic abstraction.
Deterministic Guardrails & Verification
Real-time citation verification, PII redaction engines, prompt injection firewalls, and NeMo Guardrails ensuring outputs are strictly factual and aligned with enterprise policy.
Multi-Agent Orchestration & Tool Calling
Autonomous workflow agents that call internal ERPs, databases, and REST APIs. Graph-based orchestration with human approval checkpoints for high-impact transactions.
Continuous Observability & Telemetry
Full token tracing, semantic drift monitoring, cost-per-query tracking, and user feedback loops via LangSmith and OpenTelemetry to continuously improve model performance.
The 4-Sprint Enterprise AI Deployment Lifecycle
A structured, milestone-driven engineering methodology that moves your team from raw enterprise data to battle-tested, monitored production AI in weeks.
Data Ingestion & Sovereignty Audit
We audit your proprietary data silos, clean unstructured documents, mask sensitive PII, and architect the optimal vector storage and security perimeter.
Retrieval Tuning & Model Alignment
We calibrate chunking strategies, set up hybrid dense-sparse search, and train custom cross-encoder rerankers tailored to your domain vocabulary.
Automated Evals & Guardrail Hardening
We build custom golden test datasets, implement NeMo guardrails, run red-team vulnerability tests, and establish citation-checking thresholds.
Production MLOps Deployment & Telemetry
We containerize the pipeline, deploy on private vLLM or cloud endpoints, integrate LangSmith tracing, and configure continuous drift alerts.
Built for Mission-Critical Enterprise Use-Cases
From automated financial reconciliations to real-time predictive risk scoring, we engineer intelligent AI systems that create unfair competitive moats.
Autonomous Workflow & Document Intelligence
Eliminate manual data entry. Extract, cross-reference, and reconcile unstructured invoices, medical records, and legal contracts with 99.2% precision.
Enterprise AI Copilots & SOP Chatbots
Deploy intelligent internal copilots grounded exclusively in your proprietary engineering docs, compliance policies, and internal wikis.
Predictive Analytics & Risk Forecasting
Custom time-series neural networks that accurately predict inventory demand, customer churn, and equipment failure before they impact margins.
Real-Time Fraud & Anomaly Scoring
Sub-20ms neural evaluation of transactional streams to block payment fraud, account takeovers, and synthetic identity exploitation.
Semantic Vector Search & Smart Recommenders
Upgrade keyword search to intent-driven semantic vector search across millions of SKUs or internal files, boosting discovery and conversion.
Real-Time Voice AI & Speech Synthesis
Sub-300ms latency conversational voice bots that handle complex customer phone calls with natural turn-taking prosody and multilingual support.
How Different AI Approaches Compare
We help you choose between public cloud APIs, dedicated hybrid RAG, and private on-premise models.
| Evaluation Metric | Amethyst Sovereign AI | Generic API Wrapper | Off-The-Shelf SaaS | Internal In-House DIY |
|---|---|---|---|---|
| Data Sovereignty | 100% Private (Air-Gapped VPC) | Sent to 3rd Party Clouds | Shared Multi-Tenant | Complex Maintenance |
| Hallucination Control | Citation-Backed & Guardrailed (< 0.8% error) | 12% – 18% (Uncontrolled) | 8% – 15% (Opaque) | Unpredictable / Non-Audited |
| Domain Accuracy | Grounded in Private SOPs & Data | Generic Knowledge Only | Rigid Generic Templates | Slow to Iterate |
| Query Latency | < 60ms P95 Vector Retrieval | 300ms – 1200ms | 500ms – 2000ms | Variable Latency Spikes |
| Cost at Scale | Predictable Fixed Compute | Exponential Per-Token Bills | High Per-Seat Recurring Fees | High Salary & GPU Overhead |
Production AI Case Studies
Explore intelligent systems, automated pipelines, and sovereign data intelligence engineered by Amethyst Developers.
Synapse — Autonomous AI Workflow Automation
Multi-agent task orchestration, autonomous document processing, and human-in-the-loop review pipelines built on private data.
MarketPulse — AI-Powered Web Intelligence
Automated large-scale market data scraping, semantic structuring with vector embeddings, and real-time regression pricing analytics.
Frequently Asked Questions
Everything you need to know about enterprise data privacy, model architectures, and implementation timelines.
Never. We enforce strict enterprise zero-data-retention (ZDR) agreements. Your data is encrypted in transit and at rest, and is never used to train public foundation models. For clients with sovereign requirements (defense, banking, healthcare), we deploy open-weight models (Llama, Mistral, DeepSeek) completely within your private VPC or on-premise bare-metal servers.