30-day free trial on all Orbit apps — no credit card required
Start trialNo-code mapping — paste samples, describe intent, ship validated rules.
MAPR AI turns natural-language mapping intent into precise EDI, JSON, XML, CSV, and IDoc transforms — validated against your data before any rule goes live.
30-day free trial · No credit card required
Work log
AI proposal
X12 850 → IDoc ORDERS05
178 mapping rules proposed
Dry-run
All samples passed
Hours of mapping work compressed into minutes by MAPR AI
Source and target formats — X12, EDIFACT, IDoc, XML, CSV, JSON
Every rule verified against your real samples before going live
MAPR runs once at build. BPI executes the rules in production.
Industry first
iPaaS AI suggests fields. MAPR AI builds, dry-runs, and repairs complete mapping rule sets — validated against your data before anything reaches production.
Proof artifacts
MAPR is compelling because the output is inspectable. Evaluators can review the generated rules, dry-run evidence, repair trail, and promotion controls before trusting it with production work.
Direct mappings, transformation expressions, constants, loops, and fallbacks are drafted as reviewable rules.
Each rule is tested against representative samples so teams can see resolved values, skipped fields, and failures before promotion.
Low-confidence or failing rules can be repaired and rerun, preserving the iteration trail for review and audit.
MAPR runs at design time. Production flows execute approved rules, with rollback available through mapping history.
Trusted by mapping teams worldwide
The mapping agent
MAPR AI doesn't suggest mappings — it builds them. Hand it two sample payloads and a sentence of intent. It parses both schemas, drafts a complete rule set, dry-runs against your samples, repairs failures, and applies the live mapping in your IDE.
MAPR runs at design time. The rules it generates execute inside Orbit BPI's runtime — with no AI in the production path.
Work log
AI proposal
X12 850 → IDoc ORDERS05
178 mapping rules proposed
Dry-run
All samples passed
How it works
From paste to publish, mapped by AI, verified by dry-run, and ready to ship into your BPI process flow.
X12, EDIFACT, JSON, XML, IDoc, CSV, or flat-file sample payload
Pick a schema, paste a sample, or describe the target in plain English
MAPR drafts transformation rules — direct paths, constants, loops, and fallbacks
Run against your samples. Repair anything that doesn't match. Iterate.
Promote the rule set into your BPI mapping IDE. Production runs them.
Before vs after
Real capabilities
MAPR understands schemas, nested structures, and complex B2B formats. It writes the same kind of rules a senior integration engineer would write — and dry-runs them before you sign off.
MAPR AI
Orbit Pilot
Doc Insights
Schedule Asst.
9 tools exposed — connect Claude, Cursor, or Copilot to your integrations.
MAPR reads field trees, repeated groups, and target structure before drafting rules.
Generated rules follow Orbit runtime conventions — fallbacks, conditionals, and formatting included.
Repeated rows, nested segments, sibling fields, and target arrays stay connected to the right driver.
Every proposed rule is dry-run tested. Failures trigger automatic repair attempts before review.
Validation & governance
MAPR is an agent for production mappings. Every drafted rule is dry-run verified, versioned, reviewer-approvable, and rolling back is one click.
Every proposed mapping runs against your representative samples first. Resolved values, skipped fields, and errors surface before any rule reaches production.
MAPR emits structured diffs so a reviewer can approve / reject specific rules, not the whole mapping. Audit trail captures every decision.
Every AI-drafted version is captured in the mapping history. Roll back to the previous active version in one click if something breaks downstream.
90-second tour
What integration engineers ask before adopting AI-powered mapping for their B2B and ERP workflows.
No-code integration mapping lets teams connect data formats without writing custom transformation scripts. With MAPR AI on CINTAP Orbit, you paste sample payloads, describe intent in plain English, and receive a complete validated mapping rule set — ready for reviewer approval before go-live.
Typical iPaaS AI copilots suggest individual field mappings. MAPR AI builds complete mapping rule sets end-to-end, dry-runs them against your actual samples, repairs failures, and prepares reviewer-ready output — not partial suggestions.
No. MAPR AI runs at design time to draft and validate mapping rules. Approved rules execute inside Orbit BPI's production runtime — with no AI in the live integration path.
Bring two sample payloads — your hardest current mapping. We'll run MAPR AI on them live, dry-run the rules, and review the output together. 30 minutes. Engineer-led.
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Agentic Mapping Engine