Agent Setup

Build Agents Through Conversation, Not Forms

Describe what you need in natural language. Upload your SOPs. AI asks clarifying questions as needed. The workflow builds in the background—all steps, logic, integrations, and prompts generated automatically. Iterate until it's right.

Build

From idea to production-ready agent

Three paths to get there: start from templates, build through conversation, or use the visual flow builder. All three produce production-ready agents with full workflow logic, integrations, and testing built in.

Templates for common workflows

Invoice processing, email triage, customer service, data extraction. Pre-built and proven. Customize for your specifics.

Templates

Visual flow builder

Drag nodes, connect them, configure parameters. See changes in real-time. Business users build what they need without code.

Visual flow builder

Document upload for agent memory

Upload SOPs, transcripts, process manuals. Files go into agent memory where AI tools can access them during execution.

Document Memory

Conversational agent building

Talk to AI. It asks clarifying questions. You answer. It builds the workflow. Iterate through conversation until it's right.

Conversational Chat UI mock
We collect NPS surveys monthly. I want to automate tracking...
Got it! I can see your survey data. Let me create an agent...

1500+ integration connectors

SAP, Oracle, Salesforce, Workday. Already built. OAuth configured. Connect to your systems in clicks.

Integrations
W
SAP
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Test before you ship

Run with real data before deploying. See exactly what happens at each step. Catch problems before production.

Test Interface

Deploy with one click

Build → Test → Publish. API endpoint generated automatically. No separate deployment pipeline.

Build
Test
Publish
Deploy

Solution engineer support

Complex setup? Our team helps. Integration guidance. Optimization advice. Not just software—guided implementation.

ReinforcedX Solution Engineers
Helping you get your AI Solutions into production
Templates
Conversational building
Visual flow builder
Upload Docs
Integrations
Testing
Deployment
SE support

Templates: Start from what works

Pre-built agents for common enterprise workflows. Invoice processing, email triage, customer service, resume screening, order processing, data extraction. Each template includes complete workflow, configured integrations, and tested prompts. Select, connect your systems, customize, deploy.

Pre-built workflows for common use cases
Tested and proven patterns
Customizable to your requirements
Templates

Conversational agent building with iterative refinement

Start with a natural language prompt or upload documents first—SOPs, transcripts, process docs. AI analyzes what you've provided and asks clarifying questions. Answer one at a time. Each answer updates the workflow behind the scenes. Iterate through chat until it's right.

Natural language prompt or document upload
Asynchronous clarifying questions
Background workflow generation
Conversational

Visual flow builder with full control

Complete control over agent workflows without code. Drag nodes onto the canvas: Start, Tool, Condition, Agent, End. Connect them to define flow. Configure each node with prompts, parameters, conditions, integrations. See changes in real-time as you build.

Drag-and-drop node placement
Real-time preview
Full logic capability (conditions, loops)
Visual Flow Builder

Document upload for agent memory

Upload SOPs, transcripts, process manuals, and runbooks directly to agent memory. PDF, CSV, TXT, JSON supported. Content becomes accessible to AI tools during workflow execution through vector embeddings and semantic search. Your documentation becomes the agent's knowledge base.

Upload to agent memory (PDF, CSV, TXT, JSON)
Vector embeddings for semantic retrieval
AI tools access documents during execution
Upload Docs

Integration setup: Connect your systems

1500+ pre-built connectors for enterprise systems. SAP, Oracle, Salesforce, Workday, ServiceNow, JIRA, Microsoft 365, Google Workspace. OAuth authentication configured, rate limiting handled, error recovery built-in. For custom systems, import OpenAPI specifications.

1500+ pre-built connectors
OAuth authentication configured
OpenAPI import for custom systems
Integrations Setup

Testing before deployment

Before deploying to production, test with real data. The test environment runs agents against your actual inputs—invoices, emails, documents. See exactly what happens at each step. Inspect node inputs and outputs. Identify edge cases. Fix issues before they reach production.

Test with real data
Step-by-step execution visibility
Edge case identification
Testing Deployment

One-click deployment

Click Publish and your agent is live. API endpoint generated automatically. No separate deployment pipeline. No DevOps tickets. Same interface for build and monitor. When you update the agent, publish again. Changes go live immediately.

One-click deployment
Auto-generated API endpoint
Instant updates
Deployment

Solution engineer support for guided implementation

Enterprise deployment isn't just software configuration. Solution engineers help with initial agent design, understanding your process, identifying automation opportunities. Integration guidance for connecting to enterprise systems. Optimization advice for improving accuracy. Training for your team.

Process design assistance
Integration guidance
Optimization advice and team training
SE Support

Making an AI agent is as easy as having a conversation

From creating an AI agent to connecting an integration, here is your guide to begin using ReinforcedX.

Guide to begin using ReinforcedX

Build an AI Agent with a conversation
| Agent Setup with ReinforcedX

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Start building custom AI
agents to automate processes

Join our platform and start building AI agents for various types of automations.

FAQ

Questions teams ask about agent setup

What does agent setup actually involve?

We design the workflow, build the agent and the evaluation around it, run it in shadow mode against real traffic, then hand it over with a runbook. You end up owning a running system for agent setup plus the evidence it works, not a proof of concept that needs rebuilding.

How long before agent setup is live?

Four weeks is the standard implementation: discovery in week one, environments in week two, a shadow-mode pilot in week three, handover in week four. Most teams see their first agent running against real data by week three.

Do we need an ML team to run this?

No. Most clients start with strong software engineers and no ML specialists. The engagement is built so your existing team owns the system afterwards — we train them while we build rather than handing over documentation at the end.

How do you know it is working?

Every system ships with an evaluation suite: golden datasets built from your real cases, rubric-driven scoring, and regression gates in CI. Quality becomes a number you track per release rather than an opinion, and drift pages you the way a failing test would.

What happens when the agent gets it wrong?

Low-confidence and high-stakes cases route to a human queue by design. Every failure is captured with full trace context, and those traces become new evaluation cases, so the same mistake is caught automatically next time rather than recurring.

Does this run in our environment or yours?

Yours. Deployment happens inside your cloud perimeter, against your data stores and your identity provider. We integrate with the stack you already run rather than asking you to move anything into ours.

Who owns what we build?

You do. Fine-tuned weights, datasets, evaluation suites and runbooks are yours, handed over at the end of the engagement. There is no lock-in that requires us to keep the system running.

How is this priced?

A platform subscription plus a fixed-scope implementation fee, quoted in writing before work starts. Implementation is priced by engagement rather than by the hour, so a slower week costs you nothing extra.

We tried something like this before and it failed. Why would this be different?

Most failures are not model failures — they are missing evaluation, no human fallback, and no way to tell whether a change made things better. Those are the parts we build first. If we cannot define how success is measured for agent setup, we say so before taking the work.

What do you need from our team?

One process owner who knows the workflow end to end, one engineer with access to the systems being integrated, and a weekly 45-minute review. That is genuinely it — no standing project committee.

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