Custom AI Agents
No-Code ∙ Multi-Agent ∙ Automation
At a Glance
- <200ms
- Median API response time
- 4
- Supported protocols (REST, MCP, A2A, Webhook)
- 60+
- Pre-built tools and integrations
- <5min
- From zero to deployed agent
Testimonials
We replaced 3 months of agent infrastructure work with a single API call. Our agents were in production the same week we signed up. The MCP support made integration with our existing tools trivial.
The multi-agent orchestration is what sold us. We run 12 agents that coordinate on complex research tasks. Building that ourselves would have taken our team 6 months minimum.
FAQ
Is this mainly no-code?
Yes. The primary workflow is no-code configuration in the dashboard. Teams can launch AI agents without writing code. Low-code APIs and protocol endpoints are available as optional extensions when developers need custom behavior.
Can developers add custom functions later?
Yes. You can start no-code, then add low-code custom functions through APIs, webhooks, MCP tools, or A2A integrations as requirements become more advanced.
Are there rate limits on the API?
Rate limits depend on your plan. Free tier: 100 requests/minute. Pro: 1,000 requests/minute. Enterprise: custom limits. All limits are per-workspace, not per-agent. Burst capacity is available for short spikes.
How does MCP server support work?
Every agent is automatically exposed as an MCP server. Any MCP-compatible client (Claude Desktop, Cursor, custom clients) can connect to your agent and use its tools. You control which tools are exposed and which clients can connect.
Can I self-host agents on my own infrastructure?
Enterprise plans include a self-hosted option. You get the full platform runtime as a Helm chart that deploys to your Kubernetes cluster. Same API, same features, your infrastructure. Contact sales for details.
What multi-agent patterns are supported?
The platform supports hierarchical delegation (manager agents assign tasks to specialists), parallel fan-out (one agent triggers many), sequential pipelines (agents pass results forward), and collaborative loops (agents iterate together). All patterns are configurable via the API.
What is the latency for agent responses?
Median API response time is under 200ms for the platform layer. End-to-end latency depends on the LLM provider and tool calls your agent makes. Streaming responses are supported for real-time applications.
Can I choose which LLM model my agent uses?
Yes. Agents support OpenAI, Anthropic, Google, and open-source models. You configure the model per agent. Switch models without changing any other code. The platform handles provider abstraction and failover.
Is the platform SOC 2 compliant?
Yes. Sistava is SOC 2 compliance aligned and not formally certified yet. All data is encrypted at rest and in transit. We support SSO, audit logs, and data residency requirements. Enterprise plans include a dedicated security review and BAA if needed.