Each playbook walks a senior team through a concrete VDF AI build: which Custom APIs to register, which agents and intent templates to define, how Networks compose them, and how the SEEMR self-evolving router keeps quality and cost in balance over time.
A clear path from raw data and APIs to a governed, self-evolving network — the same backbone every VDF AI deployment uses in production.
Register databases, SaaS apps, and Custom HTTP APIs in VDF Data and AgentsHub.
Build feature lists, embeddings, and pgvector indexes — Private RAG, fully on-prem.
Define intent templates, agents, system prompts, and bind them into a Network.
SEEMR routes models, agents, and tools by cost, latency, capability, and energy.
Every run feeds Learning Modes — quality and efficiency improve automatically.
Build a regulator-grade rule checker that validates claims and policies against your own ruleset using a Custom API, intent templates, and tailored system prompts.
Wire a Custom API as a tool inside a VDF AI network and ground every answer in your private knowledge base — fully closed, fully on-prem.
Stand up a sovereign Copilot alternative with AgentsHub, custom integrations, domains, agents, and a production-grade chat interface.
Add your local n8n or CrewAI workflows as Custom HTTP tools. VDF AI Networks serve them via internal MCP, discover capabilities, and orchestrate them with agent networks.
Index Confluence, Jira, and GitHub into a Private RAG layer and let a multi-agent network triage tickets, draft replies, and surface runbooks.
Decompose KYC and AML cases into intent-driven sub-tasks, route them through specialist agents, and log every decision with a SEEMR-governed audit trail.
Operate a fully air-gapped classification network with on-prem SLMs, human-in-the-loop review, and per-domain policy enforcement.
Connect OSS/BSS APIs as custom tools, correlate alarms with vector-indexed runbooks, and let agent networks recommend the right remediation playbook.
Use the built-in `code_review`, `pr_review_assistant`, and `github` MCP tools to triage pull requests, surface risk, and accelerate engineering throughput.
Combine OCR, semantic search, business-rule agents, and approval routing into one on-prem network that processes claims with full traceability.
Vectorize your contract library, run clause extraction and redline suggestions through purpose-built agents, and keep every document inside your network.
Treat MES and ERP endpoints as Custom HTTP tools, correlate live signals with quality SOPs, and let an agent network propose corrective actions.
Centralize HR policies, benefits, and onboarding flows behind a private chat experience powered by domain-scoped agents and Living Knowledge.
Register your CRM (Salesforce, HubSpot, or custom) as a Custom API tool, ground responses in account context, and let agents draft prospecting plays on demand.
Build a Living Knowledge graph of CMC, clinical, and regulatory documents and orchestrate specialist agents that draft and validate submission sections.
Bring agents you already built on IBM watsonx, Microsoft Copilot Studio, Salesforce Agentforce, or Azure AI Studio into VDF AI Networks as Custom HTTP tools and orchestrate them alongside native agents.
Scan source code, infrastructure, and prompts to build an AI System Register, classify risk, and surface compliance gaps — turning the EU AI Act into a tractable engineering problem.
Download the on-prem Docker image, install the stack, create a superadmin, and start your first agent — with two months free on the VDF AI Sovereign tier.
Bring a real-world AI problem. Our team scopes, builds, and ships a working VDF AI application on your infrastructure within 48 hours — using the same platform you operate.
Build a self-learning, multi-agent e-commerce backend without writing glue code. Create agents manually, via LLM prompt, or on-the-fly — and let them improve every checkout.
Use VDF Data to build evaluation feature lists, generate fine-tune datasets in OpenAI/Anthropic/JSONL formats, train an on-prem SLM, and route to it through SEEMR.
A pragmatic path from a LangChain or LangGraph project to a governed VDF AI Network — keeping your tools, replacing the runtime, gaining SEEMR routing and observability.
Stitch separate Confluence, Jira, GitHub, and SharePoint footprints into one Living Knowledge graph — with per-BU scopes, shared retrieval, and consistent governance.
Wire market data, internal positions, and research notes into a low-latency multi-agent network that surfaces signals and explains them — all inside the bank perimeter.
Combine VDF AI's built-in web_crawler and web_search MCP tools with a Private RAG of your internal documents to produce briefings analysts can trust.
Every playbook inherits SEEMR's five learning modes: model governance, agent personality evolution, knowledge-graph integration, cost optimization, and energy-aware routing. That's why a VDF AI deployment keeps improving long after the first week of go-live.
Tell us what you’re trying to achieve—governed AI Networks, enterprise RAG, deep integrations, or on‑premise deployment. We’ll help you map the right architecture, security posture, and rollout path. If you’re moving beyond AI pilots and need scalable, auditable execution, reach out—our team is ready to help.