Solutions / Compound AI

Chain models and tools into governed agents.

Build multi-step AI workflows that call tools, branch on results, and chain specialist models together — all passing through the ManyLayers gateway for guardrails, budget enforcement, and a complete audit trail.

The problem

Single-model prompts plateau quickly on complex tasks.

Real business problems — contract review, customer escalation triage, code generation with verification — require multiple steps, tool lookups, and model handoffs. Stitching these together with ad-hoc glue code creates ungoverned pipelines with no observability, no budget controls, and no way to measure quality improvements systematically.

The outcome

Governed multi-model workflows with measurable quality.

ManyLayers Workspace lets you compose agents visually, wire in MCP tools, and apply conditional logic between steps. Every model call in the workflow passes through the gateway — so guardrails, spend limits, and audit logs apply automatically. Evals and ELO leaderboards tell you whether workflow changes actually improve outcomes.

Capabilities

Everything you need to build production-grade agents.

Multi-Model Chaining

Wire together GPT-4o, Claude, Gemini, and open-weight models in a single workflow. Each step can use a different model optimised for that subtask — classification, generation, verification — and results pass automatically to the next node.

MCP Tool Calling

Native support for the Model Context Protocol. Agents discover and invoke tools — web search, SQL queries, REST APIs, code execution — without custom orchestration glue. Add new tools via a standard interface.

Conditional Branching

Route agent execution along different paths based on model output, confidence scores, or custom rules. Branch on classification results, escalate to a larger model on low-confidence responses, or terminate early when criteria are met.

Evals & ELO Leaderboards

Run automated evaluations after every workflow change. A/B comparisons are scored and ranked on an ELO leaderboard so you can see whether a new model or prompt actually improves quality before shipping.

Governed Execution

Every tool call and model request passes through the ManyLayers gateway — guardrails, PII firewall, and budget limits apply uniformly to agentic workloads, not just direct API calls.

Parallel Steps

Fan out independent subtasks to run concurrently and collect results before the next stage. Reduce end-to-end latency on complex pipelines without managing threads or queues yourself.

Execution model

How a governed agent workflow runs.

01
Define workflow nodes: models, tools, branches, and conditions
02
Input arrives — gateway applies guardrails and PII checks
03
Workflow engine fans out parallel steps and sequences serial ones
04
Each model call routes through the governed gateway with budget enforcement
05
Tool results and model outputs flow into downstream nodes
06
Final output produced; evals score quality against your benchmark suite

40+

Providers available to chain steps

20+

Native tool connectors via MCP

100%

Requests governed by gateway rules

“We built a three-model contract review pipeline in an afternoon. The evals framework told us immediately which model combination gave the best accuracy — without any manual scoring.”

Head of Legal Technology — Global Professional Services Firm

Build your first governed agent workflow today.