The saving is the model you already own, on the network the data already lives in.
Dual RAG cites the source. Agents sit on your graph. Live in 2–3 days.
Voice is speech, translation, the model, then audio or a talking-avatar video.
Those agents run the next action in the frontend and the backend.
Secure APIs only. Nothing is copied, stored, or processed on our side.
On-prem, private cloud, or air-gapped. Data stays.
We route the work. You own every byte.
On-prem, private cloud, hybrid, or air-gapped. Every byte stays.
Secure APIs in. Answers out. You keep every byte.
RAG, agents, and guardrails in 2–3 days. >90% lower cost. >80% faster than a custom build. Then generate, verify, benchmark, and deploy the model.
Siloed tools, manual integration, months of delay
No-code wizard, then generate, verify, benchmark, and deploy
Databases, models, and RAG stay in your network. On-prem, private cloud, or air-gapped.
Connect hundreds of data sources into AI-ready datasets—entirely within your environment.
Every request authenticated and authorized. No implicit trust, no unauthorized data exposure.
Deploy on-premises, private cloud, hybrid, or air-gapped. You own every byte, always.
Architecture designed for the strictest regulatory environments from day one.
Architecture designed for strict regulatory requirements. Compliance-ready for GDPR, HIPAA, SOC 2 Type II, ISO 27001, and FINRA.
No code. Connect data and models. We build RAG, the agent graph, guardrails, and the APIs.
Link databases, files, and APIs securely
Connect your AI models
Automatic pipeline creation
Security & compliance built-in
Multi-agent graph & access control
Validate before deployment
Production-ready endpoints
Vector RAG and Graph RAG. Indexing, embeddings, and routing stay under your control.
Connect to your data sources via secure APIs
Semantic document segmentation
High-quality embeddings generation
Build knowledge graphs for agentic workflows
Lightning-fast similarity search
Held-out data before it goes live. SLM or LLM, then vLLM or Ollama, on the host you register.
Start from a base model, or train from scratch. Set the purpose—legal notes, clinical reports, petitions—and, when the model must produce files, fill a template you supply.
Compare the fine-tuned model with other candidates on a golden dataset. Each run produces scores, a judgement, and a verdict.
Take the Hugging Face repo from a completed fine-tune and deploy it with vLLM or Ollama. You get an OpenAI-compatible endpoint and live stage progress.
The same boundary as the rest of EazyAI. The platform coordinates the job. The dataset, checkpoints, and endpoint stay where you put them.
Speech, translation, the model, then audio or a talking-avatar video. The agent runs the next action in the frontend and the backend.
Your hosts. Your allowlist. Nowhere else.
Same project. Policy, RAG, and the agent graph.
One wizard. Each engine links to a project AI configuration.
Wake word in. Audio out, or the avatar talking. Agents fire CTAs in the frontend and the backend.
The same voice pattern—hear, retrieve, speak—runs on the device you place it on. Mobile, desktop, a small attendant box, or cloud. After the cabin pack is loaded, passenger turns keep working when the aircraft is offline.
STT, a small language model, TTS, and local RAG. No Postgres on the edge.
Seal the config, push the cabin pack, collect logs when a link returns.
One sealed config. The binary matches the machine you chose.
Wake or speak. Retrieve from the pack on disk. Answer aloud. Open the screen you named.
Cloud platforms sell models. EazyAI ships governed RAG, agents, and voice in days—on infrastructure you control.
| Tool | Best for | Key focus | Where EazyAI differs |
|---|---|---|---|
| EazyAI | Enterprises that want production RAG, Graph RAG, and agents quickly without a large bespoke platform team | No-code orchestration, multi-agent graph, voice agent, connectors, guardrails, teams; time-to-value in days on your stack | Opinionated product layer for applied AI apps, not a raw model API or general ML workbench |
| Microsoft Foundry | Microsoft-centric enterprise AI | Agent building & multi-model catalog | Foundry fits Azure / M365-first estates; EazyAI is vendor-neutral for data sources and deployment targets you already run |
| AWS Bedrock | Multi-model RAG apps on AWS | Ease of use & model variety | Bedrock is model access + building blocks; EazyAI adds end-to-end wizard, governance patterns, and less custom glue per use case |
| Google Vertex AI | Google Cloud ecosystem users | Multimodal AI & data integration | Vertex is GCP-native; EazyAI can sit where your databases, files, and identity already live across clouds or on-prem |
= Included/Best = Limited/Extra Cost = Not Available/Manual
RAG, agents, voice, model ops, time-to-value, lock-in. Check it against your contracts.
| Feature |  EazyAI |
Microsoft AI Foundry | AWS Bedrock | Google Vertex AI | Custom Build |
|---|---|---|---|---|---|
| Vector RAG | Built-in | Azure AI Search (extra cost) | OpenSearch/Kendra (extra) | Vertex Search (extra) | DIY |
| Dual RAG System | Yes — Unified | No | No | No | Possible |
| LLM Support | Any LLM (no limits) | Azure OpenAI focus | Bedrock models | Vertex models | Any |
| Fine-tune SLM / LLM | From your data, with benchmark | Separate fine-tune service | Custom model import | Tuning jobs | DIY |
| Deploy your model | vLLM or Ollama on your host | Managed endpoints | Managed endpoints | Managed endpoints | DIY |
| Product AI Evaluator | Benchmarks, reports, verdict | Separate eval tools | Separate eval tools | Separate eval tools | DIY |
| Voice agent | STT, translate, LLM, audio or video | Separate speech services | Separate speech services | Separate speech services | DIY |
| Intelligent Routing | Built-in auto-routing | Manual | Manual | Manual | DIY |
| Multi-Agentic Platform | Agentic graph — no code | Limited agents | Bedrock Agents | Vertex Agents | DIY |
| Agentic Graph Implementation | Built-in orchestration | No | No | No | Custom build |
| No-Code Setup | 7-step wizard | Complex integration | Complex integration | Complex integration | All manual |
| Database Support | Any SQL/NoSQL | Azure preferred | AWS preferred | GCP preferred | Any |
| Guardrails Built-in | Yes — RBAC, PII, filters | Basic IAM | Basic IAM | Basic IAM | DIY |
| Usage Limits | None | Rate limits apply | Rate limits apply | Rate limits apply | None |
| Deployment Time | 2–3 days | 4–12 weeks | 4–12 weeks | 4–12 weeks | 3–6 months |
| Vendor Lock-in | Low (portable) | High | High | High | None |
Vendor positioning evolves; validate current capabilities against your architecture and procurement rules.
Fintech, health, legal, aviation, underwriting, and finance first — then BI, support, knowledge, and voice. Open a card for the walkthrough. The data stays put.
Loans, agri, EMI, and insurance. The agent reads the file. A person binds the decision.
Prior auth, denials, coding, and the ward. A person signs. The record stays.
Pull the clause. Answer the policy question. Faster review.
Lights, dining, and entertainment at the seat. It keeps working when the link is down.
Risk, compared. Decisions backed by the case file.
Ask a finance question. Get the KPI, the report, the trend.
Ask the warehouse. Get the number, the report, the trend.
Close 80% of tickets on the first reply. Grounded. Always on.
Ask in plain language. Search docs, wikis, and databases at once.
Answers from contracts and reports, with the source attached.
Papers, data, and reports. The relevant point, fast.
Find the snippet, the doc, and the pattern. Across your codebase.
STT, translate, LLM. Audio, or the avatar talking. CTAs in the app and the service.
Access by role. A record of every turn. Not one byte leaves your network.
Secure API orchestration only—zero data copying or external storage.
Military-grade encryption at every layer of the stack.
Fine-grained permissions with PII detection and redaction.
Every query, response, and access event logged immutably.
Deploy in your VPC with full network segmentation.
Business continuity built into the platform architecture.
Compliance-ready architecture for the strictest enterprise and financial regulations.
Cost, speed, or accuracy. Agents hand off on the graph. Dual RAG checks the answer.
Natural language request
Cost · Latency · Accuracy scoring
Semantic retrieval
Relationship context
Agentic orchestration & routing
Dual RAG verified · 0–min hallucination
Specialized agents. One knowledge graph. No code. The engine routes, shares context, and hands off.
Customer queries & tickets
Contracts & compliance
Orchestrates routing, context & handoffs
Reports & analysis
Deep retrieval & synthesis
Automatically selects the most cost-effective model and data path—cutting inference spend by over 90% without sacrificing quality.
Vector RAG and Graph RAG run in parallel, cross-referencing results to eliminate hallucinations and deliver factually grounded answers.
Real-time performance scoring routes queries to the fastest available path—reducing time-to-response by over 80%.
Build a multi-agentic platform with no code—define agent roles, connect them on knowledge graphs, and let EazyAI orchestrate handoffs, tool use, and complex workflows automatically.
STT, translate, LLM. Audio, or the avatar talking. CTAs in the app and the service.
Models, databases, SaaS, files, and APIs. Every agent reads what is current.
Pre-built connectors across your entire enterprise stack—all inside your infrastructure.
Your infrastructure. Your provider. The compute stays on your account.
Individual developers, prototypes, evaluation
Small teams (5–20 users)
Large orgs (100+ users)
Organizations wanting turnkey AI solutions
Pricing is for the EazyAI software license. Your choice of LLM provider and compute costs remain under your control.
A working path in 2–3 days. Your stack. Your trail.