Agentplace
AI platform streamlines real estate management and client interactions.. [Freemium]
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What is Agentplace?
Agentplace is a no-code AI agent platform that lets individuals and teams build, deploy, and collaborate with specialized AI agents for real tasks and workflows—like having AI teammates. Users create agents through plain-language prompts in a builder, then deploy instantly to the cloud with visibility controls (public, private, or restricted). The platform covers use cases across lead routing, document analysis, scheduling, research, HR policy support, competitor research, and internal admin work.
Key features include a ChatGPT-style work environment for switching between agents and getting work done (including voice interactions), goal-directed agents that reason and adapt rather than following fixed workflow steps, MCP-native integrations for connecting to 100+ tools like Gmail, Slack, GitHub, Jira, Stripe, HubSpot, Notion, Google Drive, Salesforce, and Airtable, persistent agent memory via skills and file system, human-in-the-loop workflows where agents surface custom UI for actions requiring approval, and multi-runtime deployment (web chat, voice, CLI inside Claude Code, callable sub-agent) from a single build.
Agentplace is designed for business teams, operations teams, researchers, and non-technical users who need AI that handles exceptions, unstructured inputs like emails and PDFs, and judgment calls. It works for companies that want to automate lead generation, document processing, meeting scheduling, internal support, and research without engineering involvement. The open platform also supports engineers who want to connect custom tools via MCP and GitHub Connect.
The platform supports frontier models from OpenAI (GPT-4o, o3), Anthropic (Claude Sonnet, Claude Opus), and Gemini Pro out of the box without API keys, while also allowing bring-your-own-key setups on all plans. Teams can build their own agents from scratch or start with ready-made agent templates for common workflows.
Agentplace pricing
Pricing model: Freemium
Free: $0/month forever, includes unlimited Builder access, 1,000 agent calls/month, MCP integrations, OpenAI/Anthropic/Gemini models, and GitHub Connect. No credit card required. Pro: $29/month billed monthly, includes unlimited Builder access, 2,000+ agent calls (scales up to 5k/10k/20k/50k), MCP integrations, OpenAI/Anthropic/Gemini models, and GitHub Connect. Business: Custom pricing, includes SSO, private cloud instances, enhanced security controls, custom integrations, and dedicated support. No per-seat fees on any plan. BYOK is available on all plans.
Agentplace pros
- No-code builder—plain language prompts create agents without engineering
- Free forever tier with 1,000 agent calls/month and full builder access
- Goal-directed agents that reason and adapt, not just execute fixed workflows
- MCP-native integrations—connect 100+ tools without custom connectors
- Multi-runtime deployment: web, voice, CLI, and sub-agent from one build
- Voice interaction mode built into every agent without extra configuration
- BYOK (Bring Your Own Key) available on all plans including free tier
- No per-seat pricing—pay for agent calls, not team size
- Persistent agent memory via skills and file system across sessions
- Human-in-the-loop workflows with custom UI for approval actions
- GitHub Connect for version-controlled deployment and collaboration
- Ready-made agent templates for lead routing, scheduling, research, HR
- Instant cloud deployment with public/private/restricted visibility controls
- ChatGPT-style workspace to switch between multiple agents seamlessly
- Agents handle unstructured data like PDFs, email, and audio natively
- Scale from free to Pro ($29/mo) to Business without architecture changes
- Open platform—engineers can add custom tools and external validations
Agentplace cons
- Not ideal for teams needing only simple trigger-action automation
- No SOC 2 or HIPAA compliance certifications yet (Business tier has enhanced security)
- Visual workflow builder not available—prompt-based only, not node-based
- Newer platform compared to enterprise tools like Stack AI or Zapier
- Limited compared to Zapier's 7,000+ pre-built connector library
- Best for controlled workflows with humans in the loop, not fully autonomous execution
- No dedicated mobile app—accessed through web interface
- Custom integrations require engineering involvement for Business tier
- Agent call limits on free tier may be insufficient for high-volume use
- Self-hosted deployment not available—managed SaaS only
Frequently asked questions about Agentplace
What is Agentplace?
Agentplace is a no-code platform that lets individuals and teams build, deploy, and collaborate with custom AI agents for real tasks and workflows. Unlike one-shot chatbots, agents on Agentplace behave like teammates—they handle lead routing, document analysis, scheduling, research, and internal support. You build agents using plain-language prompts, deploy to the cloud instantly, and work with them in a ChatGPT-style environment.
How is Agentplace different from workflow automation tools like Zapier?
Zapier and Make execute predefined trigger-action steps in a fixed sequence. Agentplace builds goal-directed AI agents that reason: they plan, take actions, evaluate results, and loop until a goal is achieved. Agents handle exceptions, unstructured inputs (emails, PDFs, voice), and multi-step judgment calls without manual branching. Agentplace also adds voice mode, multi-runtime deployment, MCP integrations, and persistent memory.
What is MCP and why does it matter?
MCP (Model Context Protocol) is an open standard backed by Anthropic for connecting AI models to external tools and data sources. Instead of building custom API integrations for every tool, any app with an MCP server connects to any MCP-compatible agent instantly. Agentplace is MCP-native, so your agents automatically gain capabilities as the MCP ecosystem grows. This gives you future-proof integrations without waiting for connector libraries.
Can I use my own API keys?
Yes. BYOK (Bring Your Own Key) is available on all Agentplace plans, including the free tier. You can use your own OpenAI, Anthropic, or Gemini API keys so you pay model providers directly at standard rates. This avoids LLM markup on every call and can save hundreds per month compared to platforms that bundle model costs.
What models does Agentplace support?
Agentplace includes built-in access to OpenAI (GPT-4o, o3), Anthropic (Claude Sonnet, Claude Opus), and Google (Gemini Pro) without requiring API key setup. You can also bring your own keys for any supported provider. Model selection is configurable per-agent, so different agents can use different models based on their needs.
What is multi-runtime deployment?
Multi-runtime means the same agent you build once can run in four places without extra configuration: as a web chat interface for customers, as a voice assistant for field teams, inside Claude Code as a CLI tool for developers, and as a callable sub-agent for other AI systems. Most competitors deploy to only one runtime (typically web/API).
Do agents remember context across sessions?
Yes. Agentplace agents have persistent memory via Skills and a file system. Agents learn your processes and data over time, so they don't start from scratch every session. This allows them to build knowledge about your workflows, documents, and preferences for more intelligent assistance.
How do human-in-the-loop workflows work?
Agents on Agentplace automatically surface custom UI for any action that requires human review or approval. This keeps humans and automation working together where each works best. For example, an agent might draft a response or make a recommendation, then present a UI for a human to approve before taking the final action.
What ready-made agents can I start with?
Agentplace offers templates for AI Lead Router (captures and routes leads), AI Prioritization Assistant (reviews requests/opportunities), AI Document Analyst (extracts info and summarizes risks), AI HR Policy Assistant (answers employee questions), AI Scheduling Coordinator (manages meetings), AI Competitor Researcher (gathers competitor intelligence), AI Research Assistant (turns messy info into answers), AI Setup Assistant (guides employees), and AI Follow-up Coordinator (keeps tasks from falling through cracks).
Can I deploy agents for my team to use?
Yes. Agents can be made public, private, or restricted with visibility controls. Team members can build and manage their own agents without engineering support. You can share agents internally, deploy them for customer-facing use, or restrict access to specific users. Business plans add SSO and private cloud instances for enterprise security.