SYSTEM ONLINE // V 2.4.0 (STABLE)

Production-Deployment-Ready
Agents.
Designed, Validated, Operated.

Move from PoC to reliable production agents with clear contracts, controlled deployments, and an ops-first mindset. Design in Pronto Studio, deploy as self-contained microservices.

Built for teams that ship software—not prototypes
Stable Web API Self-Contained Microservices PoC to Production Path
LEGACY_REST_API
POST /v1/orders200 OK
TELEGRAM_BOT_V2
Incoming Message
"Analyze Q3 report..."
OPEN_WEBUI_CLIENT
Socket Connected (wss://...)
PRONTO_ORCHESTRATOR
Context Window128k / 1M
ROUTING...chain_id: 8x92
Latency: 12ms
INFERENCE_ENGINE
QWEN-2.5-72BMETAL
GEMINI 2.0CLOUD
DEEPSEEK R1DISTILL
MCP_SERVER_REGISTRY
Browser
Filesystem
ACTIVE_TOOLS
code_interpreterduckduckgo
The End-to-End Lifecycle

From Idea to Production

A clear path from workflow design to deployable services. Build in Studio, validate as PoC, harden for production, then deploy as a self-contained microservice.

01

Design in Pronto Studio

Create multi-agent workflows with defined steps and tools. Define responsibilities for each agent and make tool usage explicit through MCP servers. Build the workflow structure visually and systematically.

Agent_A
• Tool: search
• Tool: extract
• Output: JSON
Agent_B
• Tool: analyze
• KB: docs_v2
• API: ready
WORKFLOW_VALIDATED ✓
HAPPY_PATH
✓ VALIDATED
EDGE_CASE_1
✓ VALIDATED
EDGE_CASE_2
✗ NEEDS_FIX
VALIDATION_REPORT
● LIVE
Data Flow:✓ Verified
Tool Wiring:✓ Connected
Edge Cases:⚠ 1 Found
POC_FEASIBLE ✓
02

Validate a PoC

Prove the data flow, tool wiring, and workflow shape. Identify edge cases and failure modes early. Confirm feasibility before production hardening in a controlled validation stage.

03

Promote to Production-Ready

Refine the workflow into a deployable unit. Tighten input/output data models, constrain tool access, and finalize operational boundaries and behavior expectations.

I/O_SCHEMA_v2
input: strictREFINED ✓
output: typedLOCKED ✓
TOOL_ACCESS
✓ search_api (whitelisted)
✓ kb_v2 (scoped)
✗ external_db (blocked)
BOUNDARIES
• Timeout: 30s
• Max tokens: 4096
• Retry: 3x exponential
PRODUCTION_READY ✓
WEB_API
POST /v1/workflow/execute
STABLE_CONTRACT ✓
MANAGED
• Isolated runtime
• API gateway
• Zero ops
EXPORT
• Container image
• Your infra
• Full control
DEPLOYED ✓
04

Deploy as Microservice

Deploy to an isolated managed environment or export as a container image. Either path results in a self-contained microservice with a stable Web API you can integrate into real systems.

What You Build in Pronto Studio

Core Capabilities

Design workflows with explicit boundaries, structured data models, and controlled integrations. Build systems you can deploy and operate—not experiments.

01

Visual Workflow Design

Canvas-style workflow creation with defined steps, agents, and control flow. Design multi-agent processes with clear responsibilities—not improvised behavior.

02

Explicit Data Models

Define what each agent receives and returns. Set the workflow-level contract that becomes your Web API interface. Improve predictability through structured outputs.

03

Tools & MCP Servers

Configure tools as first-class capabilities. Register external systems as MCP servers. Make dependencies visible and auditable at design time—not buried in code.

04

Knowledge Bases

Connect vector databases for retrieval. Build context-aware agents with domain knowledge. Integrate RAG patterns with explicit boundaries and versioned embeddings.

05

Stable Web API

Every deployed workflow exposes a Web API defined by its input/output models. The contract stays stable while the implementation evolves—enabling safe integration.

06

Flexible Deployment

Deploy to an isolated managed environment or export as a container image. Run in your cloud, on-prem, or hybrid infrastructure—the microservice contract remains consistent.

Design & ModelsIntegration & ToolsDeployment & API
The Pronto-Sage Portfolio // v2.4

The Pronto-Sage Portfolio

A branded-house ecosystem. Pronto Studio for design, validation, and deployment (powered by Pronto-Sage Engine orchestration). Academy to teach your team with hands-on courses. Agent Factory to co-build with you from PoC to production—deployed in your environment.

FIG.01
ACTIVE
XX✓SIMULATION_COMPLETE
SYSTEM_DIAGNOSTIC
$> WORKFLOW_VALIDATED... ENGINE_ORCHESTRATING... READY_FOR_DEPLOY

Pronto Studio

Design, Configure, Validate, and Deploy Workflows—Powered by Pronto-Sage Engine Orchestration

VISUAL CANVASMulti-agent workflows with defined steps
DATA CONTRACTSExplicit input/output models per agent
TOOL CONFIGFirst-class tools + MCP servers
KNOWLEDGE BASESRAG patterns with versioned embeddings
POC VALIDATIONBuilt-in validation stage
DEPLOYMENTManaged runtime or container export
FIG.02
ACTIVE
CONTEXT_THREAD
SYSTEM_DIAGNOSTIC
$> TRAINING_MODULE_ACTIVE... HANDS_ON_LAB... TEAM_QUALIFIED

Pronto-Sage Academy

Qualification-Style Learning Program—Teach Your Team Agent System Concepts Using Pronto Studio

LEARNING LABUse Pronto Studio as hands-on lab
CORE CONCEPTSSchemas, tools, retrieval, orchestration
OBSERVABILITYOperational thinking & monitoring
POC VS PRODReal difference between stages
DEPLOYMENTManaged vs container export paths
OUTCOMETeam qualified to build production agents
FIG.03
ACTIVE
PUBLICSECURE
SYSTEM_DIAGNOSTIC
$> CO_DESIGNING... VALIDATING_POC... HARDENING... DEPLOYING_TO_PRODUCTION

Pronto-Sage Agent Factory

We Build With You, Then Deploy in Your Environment—PoC to Production, End-to-End

CO DESIGNDesign together in Pronto Studio
POC VALIDATIONValidate quickly, identify edge cases
HARDENINGRefine models, constrain tools, finalize boundaries
DEPLOYMENTManaged runtime or your infrastructure
INTEGRATIONConnect with your APIs & security policies
OUTCOMEDeployable microservice with stable Web API
Strategic Advantage

What Makes Pronto-Sage Different

Most agent projects fail at the handoff from prototype to production. Pronto-Sage provides a repeatable path: stable Web APIs, explicit data contracts, clear dependency mapping, and flexible deployment—managed runtime or container export.

Production Mindset by Design

Pronto-Sage treats agents as software you operate. Stable interfaces via Web API. Explicit inputs/outputs instead of free-form everything. A lifecycle that deliberately separates PoC from production readiness.

GPT-4
LLAMA-3

Deployment Control

Choose your operating model: isolated managed environment for fast delivery, or container image export for full control in your infrastructure. Either way, it's a self-contained microservice.

KZ_NODE_ACTIVE

Explicit Dependencies

Clear dependency mapping through tools and MCP servers. When workflows integrate with external systems, those connections are explicit in configuration—making audit and change review tractable.

Stable Web API

Every deployed workflow exposes a Web API defined by its input/output models. The contract stays stable while implementation evolves—enabling safe integration with existing systems.

Reliability Without Hype

Build systems that can be integrated with existing APIs and security boundaries. Operated with repeatable change control and clear ownership. Hardened from PoC into production-deployment-ready agents.

The Engineering Stack

Built on Open Standards.

No proprietary black boxes. Containerized, model-agnostic, and graph-orchestrated. We use the tools you trust.

Orchestration & State

LangGraphLangChain

Graph-based state management ensures agent loops are deterministic. Prevents infinite recursion and guarantees loop-safe, reliable task completion.

Infrastructure & Runtime

DockerKubernetes

Every agent is containerized for total immutability. K8s orchestrates high-availability clusters, ensuring horizontal scaling under heavy inference loads.

Inference Layer

Llama 3GPT-4oClaude 3.5

Decoupled reasoning engine. Our "Model Router" dynamically dispatches simple tasks to cheaper open models and complex reasoning to SOTA proprietary models.

Semantic Memory

PineconeWeaviate

Long-term semantic memory using high-dimensional vector stores. Allows agents to recall past interactions and query internal knowledge with zero hallucination.

System_Core // orchestration
LangGraphv0.1.0
LangChainv0.2.0
Core Use Cases

From Design to Deployment

Design in Pronto Studio → validate as PoC → deploy as a self-contained microservice via Web API. Real workflows solving real problems.

Customer Support Workflows
UC_SUP // WORKFLOW

Customer Support Workflows

STATUS: TRIAGE_ACTIVE

Triage → retrieve context → propose resolution → handoff or execute. Design in Pronto Studio, validate as PoC, deploy as a self-contained microservice via Web API.

Document Workflows

02

documents
Research & Analysis Flows

03

research
Frequently Asked Questions

Common Questions

Understanding Pronto-Sage's approach to deployment, integration, and the journey from PoC to production.

System_Health
SOVEREIGNTY_CHECK
[secure]
NETWORK_ISOLATION
[air-gapped]
MODEL_INTEGRITY
[verified]
UPTIME: 99.99%●

No. Pronto-Sage focuses on the path from PoC to production-deployment-ready agents and deployable services. You design workflows in Pronto Studio, validate them as a PoC, then harden them into production services with stable Web APIs.

Compliance Verified
Encrypted At Rest

Build an Agent System
You Can Actually Deploy.

From PoC to production with clear contracts and controlled deployments.

Self-contained microservices with stable Web APIs.

Platform Walkthrough Available

Ready to ship production agents?

Start with a PoC in Pronto Studio, harden it into a production-ready service, and deploy it in the environment you control—managed or exported.

Engage Agent Factory
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