Agentic AI for Supply Chain Enterprises

We >> shift
your supply chain
with AI Agents.

RShift deploys agentic AI that connects to your SAP systems, Jira boards, meeting notes, and internal docs — turning trapped institutional knowledge into autonomous workflows that drive revenue.

Start a conversation See what we build
// your data, your context, your agents
01 from rshift import Agent
02
03 agent = Agent.connect(
04 sources=[
05 "sap://procurement",
06 "jira://supply-ops",
07 "notes://weekly-sync"
08 ],
09 model="claude-sonnet",
10 guardrails=True
11 )
12
13 agent.deploy() >> production

Your supply chain runs on institutional memory that walks out the door

Every procurement decision, supplier negotiation, and demand signal gets captured somewhere — SAP transactions, Jira tickets, meeting notes, Slack threads. But it stays trapped, siloed, and invisible to the people making decisions right now. RShift extracts this context and feeds it to Claude, creating AI agents that understand your supply chain as deeply as your best planners.

01

SAP / ERP

Years of PO history, supplier performance, inventory movements — locked in T-codes your planners can't query fast enough

>> context
02

Jira / Tickets

Every supply disruption, every workaround, every escalation pattern — buried in tickets no one reads twice

>> context
03

Meeting Notes

Supplier negotiations, demand signals, inventory decisions — made in meetings, forgotten by Monday, never reaching the floor

>> context
04

Slack / Email

Why that PO was delayed, why that supplier was blacklisted, why that SKU was discontinued — buried in a thread from 2022

>> context

AI agents built for supply chain operations

01

Autonomous Procurement Agents

Agents that monitor SAP purchase orders, detect anomalies, surface supplier risk from historical patterns, and draft POs for approval — cutting manual processing time from days to minutes.

SAP MM → Claude → Action
02

Supply Chain Knowledge Layer

We pipe your Jira, Confluence, meeting transcripts, and SOPs into Claude via MCP — so your planners can ask "why did we stop using Supplier X?" and get a real answer in seconds.

Jira + Notes → RAG → Answers
03

Demand & Inventory Copilots

Custom AI copilots that combine ERP signals with external demand context — improving forecast accuracy, flagging stockout risk before it happens, and recommending reorder actions.

ERP + Context → Claude → Decisions

From discovery to production in weeks

01 — DISCOVER

Map your data landscape

We audit your SAP modules, internal tools, and communication channels to identify where the highest-value context lives — and where AI agents can create the most impact.

>>
02 — CONNECT

Build the context layer

Using MCP and custom integrations, we connect Claude to your enterprise data sources — creating a rich context layer that makes AI agents as knowledgeable as your senior team.

>>
03 — DEPLOY

Launch autonomous agents

We deploy, monitor, and iterate on AI agents in production — with human-in-the-loop controls, audit logging, and continuous optimization based on real outcomes.

Context is the competitive advantage

✕ Generic AI consulting

Generic chatbots with zero supply chain context
6-month POC cycles that never reach your ERP
AI that hallucinates because it's never seen your SAP data
Expensive platforms that sit on top of your data, not inside it
Vendor lock-in that makes switching painful in year two

>> The RShift way

Agents trained on YOUR SAP history, YOUR supplier data, YOUR SOPs
Working prototype touching real ERP data within two weeks
Production-grade from day one — not a demo that gets retired
SAP-native integration (MM, SD, PP, WM) built by people who know it
Open standards (Claude API + MCP) — swap, extend, own your stack

Global delivery, local expertise

SAP Oracle ERP Microsoft Dynamics Snowflake Coupa SAP Ariba Blue Yonder Kinaxis + your stack

Ready to unlock your enterprise data?

info@rshift.co