Complex Transformations Co-Pilot Agent Data Accuracy

Name: Put It Forward Explained: Head of Product
Uploaded: 2024-07-14T00:00:00+00:00
Duration: 2 min 9 s
Channel: Put It Forward
Description: Put It Forward head of product, Mark Cowan shares a brief overview of the platform, intelligent automation. Focused on how we can make better decisions with the todays data and systems to drive better outcomes.

For integration teams - converts natural language into transformation logic & rules in seconds.

Convert plain-language rules into validated transformation functions with predictive AI
Eliminate manual coding for field mapping, conditionals & multi-step data logic
Reduce transformation build time by 70% across 500+ connected system integrations
"2-day implementation" guarantee - Most clients go live in days, not months
SOC 2 + ISO 27001 compliance - Enterprise-grade security and governance built-in

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Conversational Data Transformation & Business Rule Automation in Action

Three micro-scenarios showing how the Complex Transformations Co-Pilot Agent eliminates hand-coded logic, mapping errors, and transformation backlogs.

Auto-Generate Multi-Step Transformation Logic

Cut transformation build time by 70% - natural language to validated functions in under 60 seconds per rule.

Scenario: An integration team maintains 40+ active connectors across CRM, ERP, and marketing systems. Each new field mapping or business rule requires a developer to write custom logic. Backlog averages 3 weeks. Errors in hand-coded transformations cause 12% of sync failures monthly.

Solution: The Co-Pilot agent accepts plain-language descriptions of business rules inside Integration Designer. Predictive algorithms parse intent, generate transformation functions, and validate output against source/target schemas before deployment. No code required from the user.

Results: Transformation build time dropped by 70%. Sync failure rate from logic errors fell from 12% to under 2%. Integration backlog cleared from 3 weeks to 3 days. Non-developers now build production-grade rules independently.

Business Rule Validation Automation Use Case

Validate & Optimize Existing Business Rules

Reduce transformation errors by 85% - predictive validation catches logic flaws before data hits downstream systems.

Scenario: A mid-market company has 200+ business rules across its integration layer. No validation exists pre-deployment. Bad rules propagate dirty data into billing, reporting, and CRM, costing 15+ hours per week in manual cleanup and 8% revenue leakage from invoice errors.

Solution: The Co-Pilot agent scans existing transformation logic using predictive analytics to detect conflicts, redundancies, and schema mismatches. It recommends optimizations, flags risky rules, and simulates outputs against sample data sets before any change goes live.

Results: Transformation errors dropped by 85% within 60 days. Manual data cleanup time fell from 15 hours to under 2 hours per week. Invoice accuracy improved to 99.6%. Rule audit time decreased from days to minutes.

Connector Onboarding Acceleration Use Case

Accelerate New Connector Onboarding

Shrink new connector setup from 2 weeks to 2 days - AI-powered auto-mapping and rule generation at scale.

Scenario: An enterprise adds 6-8 new system integrations per quarter. Each requires field mapping, data type conversions, and conditional logic. Average onboarding takes 10-14 business days per connector, consuming senior developer time and delaying go-live for downstream teams.

Solution: The Co-Pilot agent auto-maps fields using AI-powered schema matching, then generates transformation rules from natural language requirements. Predictive algorithms suggest best-practice patterns from similar connectors, pre-populating 80%+ of the configuration automatically.

Results: New connector onboarding accelerated from 14 days to 2 days average. Developer time per connector dropped by 75%. Go-live for downstream teams advanced by 10+ business days per integration. Error rate on new connectors fell below 3%.

Predict, Decide & Act - How the Complex Transformations Co-Pilot Agent Works

Complex Transformations Co-Pilot Agent workflow

From natural language requirement to validated transformation logic in 6 steps - no code, no manual scripting, no deployment delays.

Step 1 - Connect: Operates inside Integration Designer, accessing source and target schemas across CRM, ERP, ITSM, billing, marketing, and collaboration systems via 500+ connectors. Reads field definitions, data types, and existing rules.
Step 2 - Analyze: Profiles source and target data structures - detecting field types, naming conventions, format mismatches, and null patterns. Auto-maps fields using AI-powered schema matching and flags ambiguities for user confirmation.
Step 3 - Predict: Predictive algorithms parse natural language business rules into transformation functions. Suggests optimized logic patterns from similar connectors and flags potential conflicts with existing rules before generation.
Step 4 - Decide: Validates generated transformations against schemas with built-in guardrails. Simulates output against sample data. Routes clean rules to auto-deploy or flags edge cases for user review based on confidence thresholds.
Step 5 - Act: Deploys validated transformation logic directly into the integration flow. Updates field mappings, activates business rules, logs change history, and notifies teams via Slack/Teams when new rules go live.
Step 6 - Learn: Monitors transformation execution and error rates post-deployment. Feeds outcomes back into predictive analytics to improve rule suggestions. Detects schema drift and triggers alerts when source or target APIs change.

ROI Benefits: Complex Transformations Co-Pilot Agent

Quantified outcomes from replacing manual transformation scripting with predictive AI-driven Integration Designer orchestration.

Build Time Reduction: Cut transformation build time by 70% within 30 days - predictive AI converts natural language business rules into validated functions in seconds, eliminating manual scripting across all active connectors.
Error Rate Elimination: Reduce transformation-related sync failures by 85% within 60 days - predictive validation simulates rule output against schemas and sample data before deployment, catching logic flaws upstream.
Developer Productivity Recovery: Free 20+ developer-hours per week by offloading routine mapping and rule creation to the Co-Pilot - predictive algorithms handle 80%+ of configurations, per 40 active connectors.
Connector Onboarding Acceleration: Shrink new integration setup from 14 days to 2 days average - AI auto-mapping and predictive pattern matching pre-populate field mappings and business rules from similar connectors.
Data Quality Improvement: Improve downstream data accuracy to 99.5%+ - predictive analytics detect schema drift, null patterns, and format mismatches before dirty data reaches billing, reporting, or CRM systems.

Complex Transformations Co-Pilot Agent Leader

David Hrynk

Director of Program Management

“Having our global teams all working from the same page is critical to our success. Put It Forward exceeded way beyond where others died.”

Uma Asthana

Director of Operations and Technology

“What you just did for our teams' productivity and how we work was magic - you guys are rock stars, I’m truly blown away”

Udo Waibel

CTO

“Put It Forward takes us where no others could - we struggled for years with an enterprise data story - this solved it across the board”

Sarika Saoji

Marketing Platform Technologist

“For me when our internal teams tried to replicate the Put It Forward technology that was when the pin dropped … these are really smart people”

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Why Teams Choose Agentic AI Over Rules, Chatbots, and Manual Work

The Only Option Built for Safe, Explainable, Multi‑System Decisions

17 agent capabilities that matter most when choosing between rules, generic LLM chatbots, and manual processes.

Capability	Put It Forward Agent	Traditional Rules / Workflow Automation	Generic LLM Chatbot	Manual Human Process
Agent execution & scale
No‑Code Agent Configuration	Yes, configure via UI + templates	Limited, technical admin	Limited, prompt‑based only	No
Multi‑System Context Awareness	Yes, native across connected systems	Yes, with complex wiring	No, single‑channel context	Yes, but inconsistent
Data Preparation & Validation	Yes, uses integration layer transforms and validators	Build and maintain logic	No state or very limited	Yes, in people’s heads/spreadsheets
Stateful, Long‑Running Workflows	Yes, native	Limited, brittle state handling	No state or very limited	Yes, in people’s heads/spreadsheets
Enterprise Integration Footprint	Runs on the same governed integration fabric (APIs, services, on‑prem)	Build per system	Channel‑only	System by system
Decision Intelligence & Autonomy
Business Rules + AI Policies	Rules + ML + policy guardrails	Rules only	Ad hoc LLM behavior	Tribal knowledge
End‑to‑End Decision + Action	Yes, orchestrates decisions and API actions across systems	Yes, but static and brittle	Suggests, doesn’t execute across systems	Yes, but slow and inconsistent
Continuous Process Intelligence	Yes, Embedded	No	No	Manual analysis
Autonomy Modes	Simulate, Recommend, Auto‑Act Within Guardrails	Auto‑Act only, no simulation or learning	Suggest only, no structured guardrails	Manual judgment only
Trust, Control & Ops for Agents
Policy & Guardrail Management	Central policies, RBAC, data scopes	Scattered in config and code	Prompt only, no enforcement	Policy documents, inconsistent enforcement
Safe Failure Handling	Native error capture, auto‑rollback/compensation options	Limited, build your own	Opaque failures	Manual investigation & fixes
Agent Performance & Impact Analytics	KPIs, action logs, impact by process (Q2C/O2C)	Basic logs, no business KPI tie‑in	No structured reporting	Manual reporting
Explainability & Audit Trail	Why‑logs for each action, full audit trail	Limited technical logs	Nearly none	Email, tickets, inconsistent records
Agent Extensibility & Integration APIs	APIs/SDKs to embed and extend agents + integration	Varies, often product‑specific	Mostly channel APIs, not orchestration	N/A
Agent Design & Tuning Support	Full design/tuning support and best‑practice playbooks	Self‑serve / ad‑hoc	Self‑serve / ad‑hoc	Self‑serve / ad‑hoc
Agent & Integration Roadmap Alignment	Co‑evolves with connector and system API roadmaps	No / lagging	No / lagging	No / lagging

The intelligent decision automation playbook for revenue, operations and IT

IDC Put It Forward Next Generation Business Requirements

Take A Tour Of How The Agents Work

Next Best Customer Agent Activation

See how Put It Forward Predictive Analytics uses no-code Agentic AI to predict your next best customer, connect key data sources, and automate decisions that grow revenue.

Target high-potential customers and improve marketing ROI with predictive analytics.
Integrate data, create models, and orchestrate AI agents without writing code.
Keep your customer acquisition strategy continuously optimized as the market changes.

Natural Language Automation

Put It Forward’s Agentic Co-Pilot lets anyone use natural language to automate and change complex workflows, speeding decisions, easing IT bottlenecks, and enabling new AI-powered ways of working.

Trigger multi-step changes with simple conversational commands.
Boost productivity by simplifying complex tasks and reducing specialized effort.
Help business and technical teams co-create smarter, more agile processes.

Conversational AI Agents

Discover how Put It Forward's AI-powered Integration Designer uses conversation to simplify complex business rule creation.

Convert complex business rules from natural conversation into functions
Go faster without having to learn how Put It Forward works at an expert level
Reduce the costs of IT and increase the quality of your data

3-Day Agent Automation Enhancement, Not 3-Month Projects

Put It Forward Workday ServiceNow Integration Project Plan

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We all implement new technology; a transformation or automation project can be simple, targeted, or enterprise-wide.

Accelerate time-to-value and reduce risk with a proven integration plan.

Our proven methodology ensures low-risk, high-impact integrations. Most clients see measurable ROI in the first year accelerated by best practices and enterprise-grade support.

Most clients see improved intelligent automation performance within 48 hours
Zero disruption guarantee - No downtime to existing systems, pipelines or data loads

Implementation timeframes depend on scope and complexity:

Hour 1-2: Configure connection source and destination
Hour 2-36: Business rule configuration and validation
Hour 36-48: Full deployment

Put It Forward Agentic Resources

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This guidebook gives Integration Designer users a practical roadmap to implement AI agentic workflows, integrating intelligent automation and predictive analytics, to optimize business processes and decision-making.

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Two Ways To Integrate Agents

Learn how to integrate an agent into a process using two different methods via the Put It Forward Integration Designer and a direct service call. This helps both non-technical and technical teams find new revenue.

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Put It Forward’s Agentic AI Orchestration connects AI agents, data, and automation tools into end-to-end workflows so enterprises can cut cycle times, handle exceptions intelligently, and scale automation for measurable ROI in weeks, not months.

Solution: Agentic AI Orchestration

What You Should Do Next

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Complex Transformations Co-Pilot Agent - Frequently Asked Questions (FAQs)

How does the Co-Pilot Agent convert natural language into transformation logic?

The agent uses predictive algorithms trained on thousands of transformation patterns to parse plain-language business rules into executable functions. It reads source and target schemas, interprets your intent, generates the logic, and validates output against sample data - all within the Integration Designer interface. No coding or scripting is required.

Can I override or edit the transformations the agent generates?

Yes. Every generated rule is fully editable within Integration Designer. The agent operates in a human-in-the-loop mode - you review, modify, or reject any transformation before deployment. All changes are version-controlled and logged for audit. You always retain full control over what goes live.

How does the agent validate rules before deployment?

The Co-Pilot runs predictive validation against source and target schemas, simulates output with sample data, and checks for conflicts with existing rules. Rules that pass validation can auto-deploy. Rules with edge cases or low confidence scores are flagged for manual review before activation.

What systems does the agent work with inside Integration Designer?

The agent operates across all systems connected via Put It Forward's Integration Designer with 500+ connectors - including CRM (Salesforce, HubSpot, Dynamics), ERP (SAP, Oracle, NetSuite), ITSM (ServiceNow), marketing automation, billing, and collaboration tools. It reads and writes schemas for any connected source.

How do you ensure data security when the agent accesses schemas and data?

Put It Forward is built with enterprise-grade security, including SOC 2 and ISO 27001 compliance. The Co-Pilot agent operates within the same security perimeter as Integration Designer. All data is encrypted in transit and at rest. Role-based access, audit trails, and governance policies apply to every action the agent takes.

How long does it take to start using the Co-Pilot Agent?

The Co-Pilot agent is embedded in Integration Designer and available immediately to all users. No separate installation or configuration is required. Teams begin converting natural language into transformation logic on day one. Measurable build-time improvements are visible within the first week of adoption.

How does the agent improve over time?

Every transformation deployed, edited, or rejected feeds back into the predictive analytics engine. The agent learns from your organization's patterns, improving suggestion accuracy and reducing false flags. It monitors post-deployment error rates and schema drift to refine recommendations continuously.

What ROI can I expect from deploying this agent?

Organizations typically see a 70% reduction in transformation build time, 85% fewer sync errors, and 20+ developer-hours recovered per week. New connector onboarding shrinks from weeks to days. Downstream data accuracy improves to 99.5%+. ROI is visible within the first 30 days of adoption.

Complex Transformations Co-Pilot Agent Data Accuracy

For integration teams - converts natural language into transformation logic & rules in seconds.

Conversational Data Transformation & Business Rule Automation in Action

Auto-Generate Multi-Step Transformation Logic