Architecting Production-Ready
Generative AI & Autonomous Agents
We transition enterprise AI from fragile prompt wrappers into resilient, private, self-hosted neural systems. From hybrid RAG vector search across millions of documents to autonomous multi-agent tool swarms, we build intelligent software with strict data isolation, predictable latency, and full source code ownership.
Interactive AI Architecture Flow
Inspect how our systems transform raw heterogeneous enterprise data into verified, deterministic software actions. Click any stage to view architectural telemetry.
Interactive AI Architecture Flow
Click any pipeline stage below to inspect real-time data throughput, latencies, and architectural protocols.
Data Foundation
Raw files, APIs, databases & docs
AI Neural Core
LLMs, RAG vectors & agentic reasoning
Applications
Web platforms, mobile apps & APIs
People & Teams
End-users, clinicians & operators
Business Processes
Automated decisions & measurable ROI
Enterprise AI Architecture Practices
We architect solutions designed to survive rigorous production security, SOC2/HIPAA compliance, and volatile load spikes.
1. Enterprise RAG & Hybrid Vector Retrieval
Connect language models directly to live enterprise documentation, relational databases, and ERPs without training delays. We build hybrid sparse/dense retrieval pipelines utilizing Cohere re-ranking, semantic chunking, and pgvector/Milvus stores.
- Cohere & BGE cross-encoder re-ranking
- Hierarchical & context-aware recursive chunking
- Zero citation hallucination with traceable source verification
2. Private Open-Source LLM Fine-Tuning
Fine-tune state-of-the-art open weights (Llama 3.3, Mistral Large, DeepSeek, Qwen) using LoRA, QLoRA, and Direct Preference Optimization (DPO). Hosted entirely inside your private VPC or on-premise hardware with zero data sharing.
- High-throughput vLLM & TensorRT-LLM serving
- AWQ & GPTQ 4-bit/8-bit quantization for lower GPU costs
- 100% intellectual property ownership of tuned adapter weights
3. Autonomous Multi-Agent Swarms & Tooling
Move beyond simple prompts to autonomous state machines. We build specialized agent pods (using LangGraph, CrewAI, and AutoGen) that collaborate, execute deterministic SQL queries, query internal REST APIs, and trigger transactional workflows.
- Deterministic cyclic state-graphs with human-in-the-loop checkpoints
- Function calling & automated OpenAPI tool binding
- Self-correcting reflection loops to verify generated code/output
4. Intelligent Document AI & Vision Pipelines
Extract actionable structured schemas from unstructured PDFs, messy scans, handwritten medical forms, complex invoices, and engineering diagrams using vision-language models and layout analysis.
- Table extraction with hierarchical cell alignment
- Automated PII/PHI redaction before vector indexing
- Integration with ERP/CRM workflows via webhooks
5. Enterprise AI Guardrails & Semantic Caching
Deploy AI that enterprise CISOs approve. We implement NeMo Guardrails, prompt injection detection, output validation, and GPTCache semantic caching to ensure compliance while slashing API bills.
- Real-time prompt injection & jailbreak mitigation
- Semantic caching with Redis/GPTCache cutting 45% latency
- Automated RAGAS evaluation suites for production hallucination monitoring
6. Real-Time Conversational Voice AI
Build human-parity voice interactions. We engineer sub-500ms conversational duplex speech pipelines combining streaming Whisper ASR, fast token routing, and natural neural voice synthesis over WebRTC.
- Sub-500ms full turnaround latency over WebRTC
- Interruption handling & acoustic echo cancellation
- Direct SIP/telephony bridge for customer operations
Production Case Studies & Impact
See how our tailored AI architectures deliver quantifiable operational metrics in demanding enterprise environments.
Clinical RAG Knowledge Assistant
Built a private retrieval system querying 150,000+ clinical protocols, pharmacology guidelines, and patient histories. Zero patient data touches public models.
Automated Loan Underwriting Swarm
Engineered an autonomous multi-agent pipeline validating tax returns, bank statements, and credit bureau feeds against strict compliance rules.
Predictive Inventory Routing Hub
Multi-modal demand forecasting model processing regional weather, live freight rates, and historical sales to re-route cross-border shipments automatically.
Our Production AI Tech Stack
We build using battle-tested frameworks, open standards, and the fastest hardware accelerators.
Frequently Asked Questions About Enterprise AI
Transparent answers on governance, data isolation, hardware costs, and ongoing fine-tuning.
Never. When you partner with Arithmancy Infotech, we deploy models directly inside your isolated Virtual Private Cloud (AWS, Azure, GCP) or on-premise GPU servers. Zero telemetry or prompt data is sent to OpenAI, Anthropic, or external providers unless explicitly configured.
We implement a multi-layered guardrail architecture: (1) Hybrid dense/sparse RAG restricts responses strictly to retrieved source documents with verifiable citations; (2) NeMo Guardrails evaluate factual consistency before generation; (3) Self-reflection agent loops verify outputs against JSON schemas and domain rules before execution.
You retain 100% intellectual property ownership. You receive the complete unencrypted source code, dataset preparation scripts, LoRA/QLoRA adapter weights, Docker container definitions, and deployment configurations with zero vendor lock-in or recurring software licensing fees.
Yes. Using quantization formats (AWQ, GPTQ) and high-throughput engines like vLLM, a 70B parameter model can be served smoothly on standard commercial GPU clusters (such as dual NVIDIA A6000 Ada or H100s), saving tens of thousands of dollars compared to recurring SaaS API costs.