Agentic AI Infrastructure
Intelligent Assistants for Enterprise Knowledge (AI Implementation & RAG)
Smart assistant tools search your internal enterprise knowledge in seconds and support your team with time-intensive routine workflows (RAG Systems & GDPR-Compliant AI Models). We connect language models and autonomous assistants directly to your databases and internal tools, ensuring your business data stays strictly confidential (Autonomous AI Agents, Custom APIs & Vector Databases).
Are your workflows running at maximum efficiency?
We integrate agentic AI into your infrastructure to automate complex decision-making, significantly reducing operational bottlenecks and scaling your output.
Standalone chat tools fall short when business data remains isolated.
Generic chat tools deliver limited value when disconnected from your ERP and internal knowledge base. True enterprise value occurs when AI interfaces directly with company databases and operational workflows.
“Modern AI solutions go far beyond simple text generation. Autonomous assistive systems actively support your teams in daily operations: they prepare decision-ready analyses, retrieve data across enterprise systems, and streamline multi-step workflows reliably (agentic AI, API workflows & RAG architecture).”
The Autonomous Agent Protocol
We replace manual administrative tasks with highly robust, error-free synthetic labor.
Workflow Decomposition
Systematically dissecting enterprise processes into deterministic, computable logic pathways.
Agentic Scaffolding
Wiring multi-agent architectures using LangGraph to enable autonomous decision loops.
Action-Oriented Output
Integrating secure API endpoints to transform AI reasoning into physical operations.
Enterprise RAG Token Economics Calculator
Concrete Deliverables & 100% IP Ownership
No vague consulting buzzwords. Upon delivery, you maintain 100% ownership of your codebase, design tokens, telemetry pipelines, and documentation.
Production Hybrid RAG Architecture & Vector Indexing
Enterprise dense embedding pipeline combining Qdrant/Milvus vector search with BM25 lexical reranking.
Sovereign Self-Hosted LLM Infrastructure (Llama / Mistral)
Private on-premise or European cloud GPU deployments ensuring zero data leakage to third-party providers.
Hallucination Guardrails & Context Pruning Middleware
Deterministic prompt engineering layers enforcing citations, factual consistency, and structured JSON output.
Custom Agentic Workflows & Tool-Calling Adapters
Multi-step autonomous AI agents integrated directly into ERP, CRM, and ticketing endpoints.
Measurable Benchmark Telemetry
Who This Service Is Designed For
Ideal for your organization if:
- B2B enterprises and professional service firms handling sensitive internal documentation requiring GDPR-compliant AI retrieval.
- Software platforms integrating contextual LLM search, automated document intelligence, or agentic workflows into production.
- Companies requiring zero-data-leakage architecture where proprietary data never trains external third-party models.
Not suitable if:
- Isolated chat widgets without database integration.
- Organizations expecting magical AI results without structured internal knowledge bases.
- Low-context use cases where simple keyword search suffices.
Engagement Models & Delivery Sprints
Tier I: Zero-Retention API Setup & Internal AI Chat
Zero-Data-Retention API setup, prompt engineering framework, GDPR-compliant internal chat interface, basic document search prototype.
Tier II: Enterprise Vector Search & Hybrid RAG Engine
pgvector/Qdrant vector database, hybrid search (dense + BM25), automated PDF/Intranet document ingestion, source attribution citations.
Tier III: Autonomous Multi-Agent System & ERP Tool Calling
Multi-agent framework with tool calling, automated ERP/CRM actions, strict anti-hallucination guardrails, full observability monitoring.
Our 4-Step Engineering Process
Workflow Decomposition Audit
We surgically identify the manual, high-friction points in your company's processes.
Agentic Architecture
Designing deterministic logic trees and API connectors for the autonomous agents.
Integration & Sandboxing
Deploying the agents within a highly secure, privacy-compliant testing environment.
Production Hardening
Rolling out the agents with extensive logging, fail-safes, and human-in-the-loop triggers.
Frequently Asked Questions (FAQ)
What is Enterprise RAG (Retrieval-Augmented Generation) and how does it operate?
How does myquests guarantee 100% GDPR compliance for corporate AI solutions?
What does an enterprise AI implementation cost at myquests?
What is the difference between RAG and Model Fine-Tuning?
What are autonomous AI agents and what operational tasks can they execute?
How do you prevent prompt injection vulnerabilities and data leaks in corporate bots?
Which vector database is optimal for B2B enterprise applications?
How do you measure and evaluate the answer accuracy of an internal AI system?
Why do you exclusively build with Next.js, React, and Astro instead of WordPress or Typo3?
How are your project and package prices structured?
Do we own 100% of the intellectual property, code, and deliverables upon project completion?
How does day-to-day collaboration work in practice?
Do you provide ongoing support and SLAs after launch?
Transform AI into Productive Workflows for Your Team.
Let's automate the structural bottlenecks in your company.
Joint Projects