MageTech AI Forge is a self-hosted AI platform that brings chat, knowledge, agents, tool integrations and model management into a single governed workspace — so teams can prototype with AI today and ship production automation tomorrow.
Most AI projects die between a promising demo and a useful product — siloed chatbots, scattered tools, unclear governance, unpredictable costs. MageTech AI Forge replaces that sprawl with one connected platform where knowledge, agents, models and external tools work together under your control.
Chat, knowledge bases, agents, MCP integrations, models and execution observability live in one place with one login, one permission model and one source of truth.
Keep your data in your infrastructure. Local-first models, self-hosted PostgreSQL and Redis, and full control over what your assistants can see and touch.
A deliberate road map — foundation first, then knowledge, agents, integrations, models and usage — so value lands early and every step stays manageable.
The platform is built to answer four questions every AI initiative eventually asks.
End the sprawl of ad-hoc chatbots and disconnected assistants with one governed platform every team can share.
Keep data on-site, respect permissions, and keep an audit trail of every action — ready for security and compliance review.
Move from demo to deployed assistant in days — not quarters — with reusable agents, tools and knowledge.
Every execution, token and tool call is tracked — so you can measure impact, tune cost and keep humans in control.
People work in plain language — in chat, or through agents and APIs. No prompt engineering degree required.
The Forge picks the right model, checks the user’s permissions, and assembles the context needed to act.
Agents pull facts from your knowledge bases and call MCP tools — your database, GitHub, mail, files — to get things done.
Every run shows up in dashboards and audit logs: who, what, which model, how many tokens, and what happened.
Orchestration, identity and permissions run on the Forge core — built on FastAPI, PostgreSQL, Redis and a production-grade token-authenticated API.
Each area of the Forge has a distinct job — together they form the complete AI operating system for work.
See the pulse of your forge — members, workspaces, executions, health and live activity in one view.
Live · Phase 1Invite teams, assign Admin / Manager / Developer / Viewer roles and keep work scoped per workspace.
Live · Phase 1Conversational workspaces with memory, retrieval and tool use — your assistants, your data.
LiveIngest PDFs, docs and wikis, chunk them, and let agents answer from your own sources (RAG).
Live · Phase 2–3Build and deploy autonomous assistants — support triage, research synthesis, ops automation and more.
Live · Phase 4Connect external systems through the Model Context Protocol — databases, GitHub, email, files and more.
Live · Phase 5Manage the local and served models behind your agents — context windows, quantisation and token usage.
Live · Phase 6Watch agent runs live — succeeded, failed, running and queued — with duration and token spend per run.
Live · Phase 6Track tokens consumed per model, conversations and executions — the foundation of cost governance.
Live · Phase 7Most teams today juggle a chatbot here, a scripting tool there and a spreadsheet of prompts. The Forge replaces the pile with one governed platform.
RAG over your own documents plus MCP tool calls means answers are grounded in your data — and it can actually do things, not just chat.
Prompt-sensitive workloads can run against locally-hosted models with on-site storage — a real edge for regulated industries.
Four access roles, per-workspace scoping, JWT-authenticated sessions and a full audit log — not an afterthought.
Standardise tool access through the Model Context Protocol instead of building one-off connectors for every system.
Executions, tokens, model usage, member growth and system health — the questions stakeholders ask, answered in one place.
Every module has a named phase with realistic scope. No vapourware — you always know what’s live, next and planned.
| Capability | Scattered AI point tools | MageTech AI Forge |
|---|---|---|
| One login & permission model | Rarely | Built in |
| Answers grounded in your data | Limited | RAG on your documents |
| Can take action (tools, DB, workflows) | Manual glue code | MCP tools & agents |
| Data & model control | SaaS, off-prem | Self-hostable, local-first |
| Audit & observability | Siloed, shallow | Full audit log & dashboards |
| Predictable cost governance | Per-seat sprawl | Token & usage tracking |
Any organisation that holds proprietary knowledge, runs repetitive knowledge work, or needs AI inside its own walls can get value on day one.
Runbooks, on-call triage, internal wikis and incident summarisation — inside your own network.
Answer tickets from support playbooks, draft replies and auto-summarise escalations across channels.
Code review assistants, design-doc synthesis, PR summaries and knowledge retrieval for the whole org.
Report summarisation, policy checks and auditable AI answers that meet data-privacy expectations.
Enablement libraries, personalised outreach drafts and qualification workflows grounded in real material.
Handbook Q&A, policy drafting and onboarding partners that work from your approved sources only.
Local-first learning assistants, syllabus material retrieval and admin automation with strict data boundaries.
Ship AI features fast, keep control of cost and data, and standardise on one forge as you grow.
Value is not parked at the end of the roadmap — every phase is live and each one compounds on the last.
Auth & IAM, four access roles, workspaces, admin, dashboard, system health and the API foundation running on PostgreSQL and Redis.
Document ingestion pipelines, chunking, embeddings and retrieval so every answer is grounded in your sources.
Build and deploy autonomous agents with memory, RAG and tool delegation, plus conversational workspaces.
Connect external systems through the Model Context Protocol — databases, GitHub, email, files and more.
Manage local and served models, observe every execution with duration and token spend, and power production workloads.
Token accounting, per-workspace usage and cost forecasting to run AI with a clear budget and ROI story.
Governance and control are part of the architecture, not bolt-ons.
Secure registration with password validation, JWT sessions and continuous refresh, plus Admin, Manager, Developer and Viewer permissions.
Sign-ins, sign-outs, registrations, permission changes and (soon) every execution are recorded in an audit trail.
Environment-driven configuration, Docker deployment, PostgreSQL + Redis, and healthy/secrets-safe operational practices out of the box.
Yes. The platform is designed to run in your infrastructure — API, web and database are containerised, and sensitive AI workloads can stay on-prem with local models.
No. Non-technical teams use chat and dashboards; developers go deeper with agents, tools and the API. Role-based access meets everyone where they are.
Before modules ship, dashboards show clearly-labelled sample figures so you can evaluate the full experience. Those projections switch off in production.
Local-first models avoid per-token SaaS surprises, and the upcoming Usage module tracks tokens per model and per workspace for forecasting.
We price AI Forge as an AI engineering & agentic platform — not a chatbot. Local LLM inference is included when you run with your own infrastructure; third-party model costs are billed separately by the respective provider. Prices are indicative USD list prices.
Monthly billing · convert to annual for 2 months free on paid plans.
For developers, students, experimentation and POCs.
For individual developers and AI builders.
For teams building internal AI applications together.
For companies building internal AI applications and business agents at scale.
For larger organizations requiring private AI infrastructure and full control.
AI model usage. Local LLM inference is included when you run MageTech AI Forge with your own infrastructure (Ollama). Third-party model/API costs are billed separately by the respective provider — we do not bundle or inflate cloud inference into platform pricing.
| Feature | Community | Developer | Team | Business | Enterprise |
|---|---|---|---|---|---|
| Monthly | $0 | $29 | $99 ⭐ | $249 | Custom |
| Users | 1 | 3 | 10 | 25 | Unlimited |
| Projects | 1 | 5 | 20 | Unlimited | Unlimited |
| Knowledge bases | 1 | Unlimited | Unlimited | Unlimited | Unlimited |
| Agents | 3 | 25 | Unlimited | Unlimited | Unlimited |
| MCP tools | 3 | 25 | Unlimited | Unlimited | Unlimited |
| RAG | Basic | Advanced | Advanced | Advanced | Custom |
| AgentOps | Basic | Basic | Advanced | Advanced | Enterprise |
| Memory | Basic | Yes | Yes | Yes | Yes |
| API access | — | Yes | Yes | Yes | Yes |
| RBAC | — | Basic | Yes | Advanced | Enterprise |
| SSO | — | — | — | Yes | Yes |
| Audit logs | — | — | Yes | Yes | Yes |
| Private deployment | Yes | Yes | Yes | Yes | Yes |
| On-premise | — | — | — | — | Yes |
| Support | Community | Priority | Priority | Dedicated |
A clean progression: Free → Developer → Team → Business → Enterprise. Free for POCs, Team is the sweet spot for most teams, Business adds SSO and scale, Enterprise is fully private and on-premise. We keep the public tier structure simple and add self-hosted licensing separately.
Because self-hosting is core to AI Forge, we separate the software license from your infrastructure. You bring the hardware (GPU/CPU, PostgreSQL, Redis, Ollama or local models, storage, networking); we provide the software and support. Prices are indicative USD list prices; INR is an approximate regional equivalent.
Annual software licenses priced like the AI infrastructure market — open core at the base, enterprise capabilities and support sold separately.
| Edition | Price | What you get |
|---|---|---|
| Community | Free | Self-hosted Docker, Community support |
| Developer License | $299 / year | Email support, commercial use |
| Team License | $999 / year | Priority support, MCP allowlists, audit logs |
| Business License | $2,499 / year | SSO, advanced RBAC, deployment assistance |
| Enterprise | Custom | On-prem, SLA, dedicated support, security reviews |
MageTech provides the AI Forge software and support under the license; you own and operate your infrastructure.
Localized pricing for the Indian market. USD remains the primary international price; INR is an approximate regional equivalent.
| Plan | USD | Approx. INR |
|---|---|---|
| Community | $0 | ₹0 |
| Developer | $29 / mo | ₹2,499 / mo |
| Team | $99 / mo | ₹8,499 / mo |
| Business | $249 / mo | ₹20,999 / mo |
| Enterprise | Custom | Custom |
India pricing shown is indicative and subject to confirmation. Annual billing applies where noted.
Explore the forge yourself — see the foundation live, walk the roadmap, and put your own data to work.
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