AI Developer
Builds and deploys AI models and workflows.
- Access AI Studio
- Build models
- Test and deploy

Build, deploy, evaluate, and operate AI studios, agents, workflows, and RAG pipelines in one unified, observable, and secure browser-native platform — powered by mangollm.
Every module in mangollm shares data, memory, and telemetry in real time. Hover a node to trace its connections, or click to inspect how it plugs into the rest of the foundry.
Every module in mangollm shares data, memory, authentication, analytics, observability, and visual language — build, deploy, evaluate, and operate intelligent applications from a single unified foundry.
The primary workspace for building intelligent systems — prompts, chains, and multi-model routing in one place.
Visual environment for building AI agents with memory, tools, and behavior trees.
Unified Retrieval-Augmented Generation system spanning documents, APIs, and live data.
A visual node-based editor for orchestrating LLMs, agents, tools, and evaluations.
Purpose-built environment for evidence-based AI, grounding checks, and benchmarking.
Real-time operational monitoring across latency, token usage, and plugin health.
Monitor spend, forecast budgets, and surface optimization recommendations.
Authentication, guardrails, PII detection, and policy compliance in one console.
Every installed plugin exposes configuration, health, metrics, and API explorer.
Schedule tasks, experiments, retraining jobs, and workflow notifications.
Generate executive dashboards, compliance reports, and research papers on demand.
Manage personas, voice, tone, and conversation memory for every assistant.
mangollm's WebSim AI Foundry threads modular architecture, retrieval, orchestration, observability, and security through a single connected platform — not a pile of disconnected plugins.
Every plugin — LLM orchestration, RAG, dashboards, security, MLOps — snaps into a single shared core, exposing configuration, health, metrics, logs, dependencies, and permissions through one unified interface.
Compose LLMs, agents, tools, conditionals, memory, and vector search into node-based pipelines with the AI Workflow Builder — drag, connect, schedule, and export without writing glue code.
Design agent swarms with behavior trees, recursive verification, human escalation rules, and persona switching inside Agent Studio, enabling true agent-to-agent collaboration.
The Knowledge Hub ingests PDFs, spreadsheets, transcripts, and live APIs through a full pipeline — chunking, embedding, citation building, and a knowledge graph — for grounded, source-cited responses.
AIOps streams latency, token usage, cache hit ratio, and plugin health across line, Sankey, heatmap, and network-graph visualizations, so every workflow stays fully observable.
OAuth authentication, role-based authorization, PII detection, prompt injection guardrails, and full audit trails are enforced platform-wide from the Security Center.
Track prompt, embedding, and storage spend against forecasts and budgets, with model comparison and optimization recommendations surfaced automatically per task.
Every response ships with a reasoning path, retrieved evidence, confidence score, cost, and latency — so decisions are traceable from prompt to output.
Escalation rules route uncertain agent decisions to reviewers, keeping autonomous goals and long-running tasks accountable to real people at every checkpoint.
Regression testing, fact verification, benchmark comparison, and experiment tracking in the Research Center validate every model change before it reaches production.
mangollm's WebSim AI Foundry adapts to how you operate—whether you write models, analyze data, secure the system, or turn insight into strategy.
Builds and deploys AI models and workflows.
Analyzes data and optimizes AI models.
Manages system operations and security.
Uses AI insights for strategic decision-making.
Bring AI Studio, Agent Studio, Knowledge Hub, and every operations module together under one unified, secure platform.

Build, deploy, evaluate, and operate AI studios, agents, workflows, and RAG pipelines in one unified, observable, and secure browser-native platform — powered by mangollm.
Every module in mangollm shares data, memory, and telemetry in real time. Hover a node to trace its connections, or click to inspect how it plugs into the rest of the foundry.
Every module in mangollm shares data, memory, authentication, analytics, observability, and visual language — build, deploy, evaluate, and operate intelligent applications from a single unified foundry.
The primary workspace for building intelligent systems — prompts, chains, and multi-model routing in one place.
Visual environment for building AI agents with memory, tools, and behavior trees.
Unified Retrieval-Augmented Generation system spanning documents, APIs, and live data.
A visual node-based editor for orchestrating LLMs, agents, tools, and evaluations.
Purpose-built environment for evidence-based AI, grounding checks, and benchmarking.
Real-time operational monitoring across latency, token usage, and plugin health.
Monitor spend, forecast budgets, and surface optimization recommendations.
Authentication, guardrails, PII detection, and policy compliance in one console.
Every installed plugin exposes configuration, health, metrics, and API explorer.
Schedule tasks, experiments, retraining jobs, and workflow notifications.
Generate executive dashboards, compliance reports, and research papers on demand.
Manage personas, voice, tone, and conversation memory for every assistant.
mangollm's WebSim AI Foundry threads modular architecture, retrieval, orchestration, observability, and security through a single connected platform — not a pile of disconnected plugins.
Every plugin — LLM orchestration, RAG, dashboards, security, MLOps — snaps into a single shared core, exposing configuration, health, metrics, logs, dependencies, and permissions through one unified interface.
Compose LLMs, agents, tools, conditionals, memory, and vector search into node-based pipelines with the AI Workflow Builder — drag, connect, schedule, and export without writing glue code.
Design agent swarms with behavior trees, recursive verification, human escalation rules, and persona switching inside Agent Studio, enabling true agent-to-agent collaboration.
The Knowledge Hub ingests PDFs, spreadsheets, transcripts, and live APIs through a full pipeline — chunking, embedding, citation building, and a knowledge graph — for grounded, source-cited responses.
AIOps streams latency, token usage, cache hit ratio, and plugin health across line, Sankey, heatmap, and network-graph visualizations, so every workflow stays fully observable.
OAuth authentication, role-based authorization, PII detection, prompt injection guardrails, and full audit trails are enforced platform-wide from the Security Center.
Track prompt, embedding, and storage spend against forecasts and budgets, with model comparison and optimization recommendations surfaced automatically per task.
Every response ships with a reasoning path, retrieved evidence, confidence score, cost, and latency — so decisions are traceable from prompt to output.
Escalation rules route uncertain agent decisions to reviewers, keeping autonomous goals and long-running tasks accountable to real people at every checkpoint.
Regression testing, fact verification, benchmark comparison, and experiment tracking in the Research Center validate every model change before it reaches production.
mangollm's WebSim AI Foundry adapts to how you operate—whether you write models, analyze data, secure the system, or turn insight into strategy.
Builds and deploys AI models and workflows.
Analyzes data and optimizes AI models.
Manages system operations and security.
Uses AI insights for strategic decision-making.
Bring AI Studio, Agent Studio, Knowledge Hub, and every operations module together under one unified, secure platform.
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