Integration Architecture Best Practices for Enterprise Recruitment Technology Stacks

Your enterprise recruitment technology stack probably resembles a digital Frankenstein’s monster right now. Multiple vendors, disconnected systems, and data flowing in different directions (if it flows at all). The result? Recruiting teams juggling between platforms, compliance officers pulling their hair out, and executives wondering why their massive tech investment isn’t delivering better hiring outcomes.

Here’s the uncomfortable truth: most enterprise recruiting stacks aren’t architecturally designed—they’re assembled. But there’s a better way forward.

Establishing API-First Architecture for Scalable Recruitment Technology

Think of API-first architecture as the nervous system of your recruitment technology stack. Without it, your ATS can’t talk to your job multi-poster platform, your compliance tools remain siloed, and your analytics remain fragmented.

The foundation starts with RESTful APIs that follow consistent naming conventions and response formats. Every system in your stack should expose standardized endpoints for candidate data, job postings, application workflows, and reporting metrics. This isn’t just technical elegance—it’s a business necessity.

Consider a typical enterprise scenario: when a new position opens, your workflow should automatically trigger job distribution across multiple channels, update compliance-tracking systems, and initiate candidate-sourcing campaigns. Without proper API architecture, each of these actions becomes a manual handoff or a fragile point-to-point integration.

Smart recruitment teams establish API gateways that serve as traffic controllers for all system communications. These gateways handle authentication, rate limiting, and data transformation—crucial capabilities when you’re managing vendor relationships and ensuring system stability.

Data Standardization Protocols Across Enterprise Recruiting Platforms

Data standardization isn’t glamorous, but it’s the difference between actionable insights and expensive data chaos. Your candidate information, job requirements, and application statuses need consistent schemas across every platform in your stack.

Start with core entity definitions. What constitutes a “candidate” record across your ATS, CRM, and analytics platforms? How do you handle job classifications that need to align with OFCCP compliance requirements? These decisions cascade through every integration you’ll build.

Successful enterprises implement master data management (MDM) strategies specifically for recruitment data. This means establishing authoritative sources for candidate profiles, job taxonomies, and organizational hierarchies. When your job distribution software creates a posting, it should reference the same job codes and location identifiers used by your HRIS and compliance tracking systems.

Data validation rules become critical at integration points. Build checks that prevent duplicate candidate records, ensure required compliance fields are populated, and flag data quality issues before they propagate across systems. You’ll thank yourself during audit season.

Security Framework Requirements for OFCCP Compliance Integration

Security in recruitment technology isn’t just about protecting data—it’s about maintaining audit trails and access controls that satisfy federal compliance requirements. OFCCP regulations require detailed documentation of who accessed candidate data, when modifications were made, and how selection decisions were made.

OAuth 2.0 and SAML protocols form the authentication backbone, but implementation details matter enormously. Role-based access controls should mirror your organizational structure while maintaining the granular permissions required for compliance audits. Your integration architecture needs to log every API call, data transfer, and system access event.

Encryption requirements extend beyond data at rest and in transit. Consider field-level encryption for sensitive candidate information, especially when integrating with third-party platforms that handle background checks or assessment data. Your security model should assume that individual systems within your stack might be compromised.

Certificate management becomes operationally critical as your integration complexity grows. Establish automated renewal processes and monitoring alerts—nothing disrupts recruiting operations like expired security certificates during peak hiring seasons.

Real-Time vs. Batch Processing: Choosing the Right Integration Pattern

The choice between real-time and batch processing isn’t theoretical—it directly affects the candidate experience and the accuracy of compliance reporting. Real-time integrations excel in candidate-facing workflows, including application submissions, interview scheduling, and status updates. Candidates expect immediate responses, and delays create drop-off risks.

Batch processing remains optimal for analytics aggregation, compliance reporting, and bulk data synchronization. Your nightly batch jobs can reconcile candidate records across systems, generate diversity reports, and update job distribution channels without impacting system performance during business hours.

Hybrid approaches often deliver the best results. Use real-time APIs for immediate candidate interactions, while implementing batch processes to ensure data consistency and reporting workflows. Message queues and event streaming platforms, such as Apache Kafka, can bridge these patterns effectively.

Monitor integration performance metrics religiously. API response times, batch job completion rates, and error frequencies provide early warning signals that can prevent integration issues from impacting recruiting operations. Compliance requirements don’t pause for technical difficulties, so your architecture needs to be built with built-in redundancy and failover capabilities.

Building OFCCP Compliance Systems Through Strategic Integration

Automated EEO-1 Reporting Integration with Core HRIS Platforms

Your HRIS platform holds the demographic data goldmine that OFCCP compliance demands, but extracting it for EEO-1 reporting shouldn’t require a PhD in database management. The smartest federal contractors build direct API bridges between their core systems and reporting tools.

Modern integration architecture enables real-time data synchronization between platforms such as Workday, SuccessFactors, and compliance reporting systems. When your Job Multiposter & Distribution for connects seamlessly with your HRIS, you’re not just posting jobs — you’re building the data foundation for bulletproof compliance reporting.

The technical architecture here matters more than most HR teams realize. A properly configured webhook system can automatically flag discrepancies in demographic data before they become audit nightmares. We’re talking about catching missing race/ethnicity data at the applicant level, not six months later during report generation.

Smart contractors also implement data validation rules that run continuous checks on the integrity of their demographic data. If an employee record shows “Unknown” for race/ethnicity but has complete hire data, your system should trigger an immediate review workflow.

Applicant Tracking Integration for Adverse Impact Analysis

Here’s where most companies fumble the compliance ball: they track applicants but don’t integrate that data for meaningful adverse impact analysis. Your ATS might be capturing every application, but without proper integration architecture, you’re flying blind on the 4/5ths rule calculations that matter most to OFCCP auditors.

The integration sweet spot involves connecting your ATS directly to statistical analysis tools that can run adverse impact calculations in real time. This isn’t about quarterly reports anymore — it’s about knowing your hiring patterns as they develop.

Consider this scenario: your engineering team posts a senior developer role through your Workday OFCCP Job Posting for the system. Within 48 hours, your integrated architecture should be tracking application demographics, interview progression rates, and early indicators of potential adverse impact.

The most sophisticated setups include automated alerts when selection rates drop below statistical thresholds. Your recruiting team gains real-time visibility into patterns that could trigger OFCCP scrutiny, enabling course corrections before problems solidify.

But here’s the nuance most miss: an adverse impact analysis requires clean job-grouping data. Your integration needs to automatically categorize positions by EEO job categories, not just by internal job titles. That means your “Software Engineer III” and “Senior Developer” roles might need to map to the same EEO category for accurate analysis.

Documentation Workflow Automation for Federal Compliance Audits

When OFCCP comes knocking, you have 30 days to produce a mountain of documentation. The contractors who survive audits with minimal stress? They’ve automated their documentation workflows from day one.

Proper integration architecture means your Job Multi-Poster Platform automatically captures and stores posting duration data, reach metrics, and source diversity information. But more importantly, it tags every piece of data with audit-ready metadata.

Your workflow automation should create audit trails that connect job postings, applicant sourcing, and final hiring decisions. When an auditor asks about your outreach efforts for a specific position, you shouldn’t be scrambling through email threads and spreadsheets.

The technical architecture here involves document management systems that automatically categorize and timestamp compliance-related files. Every job posting screenshot, every diversity sourcing email, every accommodation request gets systematically filed with searchable tags.

Advanced setups include automated compliance checklists that trigger when certain actions occur. Post a job that requires VEVRAA Compliant Job Posting Solutions? Your system automatically generates the required documentation checklist and tracking mechanisms.

Cross-Platform Data Validation for Diversity Metrics Accuracy

Data integrity isn’t just a nice-to-have in OFCCP compliance — it’s the difference between passing an audit and facing enforcement actions. Your integration architecture needs built-in validation rules that catch discrepancies before they become compliance failures.

The most common data integrity issues involve demographic information that doesn’t sync properly between systems. An applicant selects “Hispanic or Latino” in your application system, but somehow appears as “Unknown” in your HRIS. Without cross-platform validation, these gaps multiply into audit vulnerabilities.

Smart integration architecture includes real-time data reconciliation processes. When demographic data moves between your ATS, HRIS, and compliance reporting systems, validation rules should flag any inconsistencies immediately.

Your OFCCP Job Multiposter & Distribution integration should include automatic weekly data quality checks. Missing EEO data, inconsistent job category mappings, or gaps in applicant flow logs all need immediate attention.

The technical foundation involves creating data dictionaries that standardize how demographic information gets stored and transferred between systems. When your job posting platform, ATS, and HRIS all use the same demographic coding, you eliminate translation errors that create compliance headaches.

Remember: OFCCP auditors don’t care about your technical challenges. They want accurate data that tells the complete story of your hiring practices. Your integration architecture either supports that story or undermines it — there’s no middle ground.

Enterprise Job Distribution System Architecture and Multi-Board Integration

Centralized Job Posting Management Across Multiple Channels

Enterprise recruiting teams juggle dozens of job boards, social platforms, and specialized sites daily. Without centralized management, you’re looking at hours of manual posting, inconsistent job descriptions, and zero visibility into which channels actually deliver results.

The architecture should center around a unified distribution hub that connects directly to your existing ATS. Popular platforms like SmartRecruiters, Greenhouse, and Bullhorn can serve as the source of truth, while your job multi-poster platform handles the heavy lifting of cross-channel distribution.

Your integration architecture needs to support real-time synchronization. When a recruiter updates a job description or closes a position, those changes should propagate across all active postings within minutes (not hours). This prevents the nightmare scenario of candidates applying for roles that no longer exist.

Consider implementing role-based posting rules as well. Different positions require different channel strategies, and your architecture should automatically route software engineering roles to technical job boards while sending retail positions to general platforms and local sites.

Craigslist and Niche Job Board Integration Strategies

Craigslist remains a powerhouse for certain sectors, particularly service industries, retail, and local hiring. But their posting requirements are notoriously finicky, and manual management quickly becomes a time sink.

Your integration architecture should automatically handle Craigslist’s unique posting flow. This means understanding their city-specific requirements, managing renewal schedules, and handling their payment processing without human intervention. Smart systems can even rotate posting times to maximize visibility during peak browsing hours.

Niche job boards present their own challenges. Industry-specific sites often have custom field requirements, different application processes, and varying approval workflows. Your job distribution software needs flexible mapping capabilities to translate your standard job data into each board’s specific format.

The key is building adaptable connectors rather than hard-coded integrations. When new job boards emerge (and they do constantly), you want the ability to add them quickly without overhauling your entire system architecture.

Application Flow Orchestration from External Sources to ATS

Here’s where most enterprises stumble: managing the candidate journey from external job boards back into your ATS. Each platform handles applications differently, and without proper orchestration, you’ll lose candidates in the handoff process.

Your architecture should create a standardized application intake process regardless of source. When someone applies through Indeed, Craigslist, or a niche board, their information needs to flow seamlessly into your ATS with proper source attribution and campaign tracking intact.

Build in redundancy too. If the direct ATS integration fails (and it will occasionally), your system should queue applications and retry automatically. Nobody wants to explain to hiring managers why qualified candidates disappeared into the digital void.

Consider implementing application status sync as well. When recruiters update candidate status in the ATS, relevant job boards should receive those updates to prevent continued outreach to candidates who’ve already been hired or rejected.

Performance Tracking and Analytics Integration for Recruitment ROI

Without proper analytics integration, you’re flying blind when it comes to recruitment spend. Your architecture needs to capture performance data from every channel and feed it back into centralized reporting systems.

Track beyond basic application volume. Quality metrics matter more than quantity. Which job boards deliver candidates who actually make it through your screening process? Which channels produce hires that stay longer than six months? Your integration should capture this data automatically.

Real-time cost tracking is crucial, too. If you’re spending $500 monthly on a job board that hasn’t delivered a single qualified candidate in three months, you need to know immediately. Build automated alerts for underperforming channels and budget overruns.

Integration architecture recruiting demands sophisticated reporting capabilities. Your system should generate executive dashboards showing recruitment ROI by channel, department, and job type. This data drives strategic decisions about future recruiting investments.

Duplicate Detection and Candidate Deduplication Systems

Multi-channel posting creates inevitable duplicate applications. The same candidate might apply through LinkedIn, your company website, and Indeed for the same position. Without deduplication, you’ll waste time reviewing duplicate profiles.

Your enterprise recruitment technology stack needs intelligent matching algorithms that can identify duplicates across different data formats. Email addresses are obvious matches, but smart systems also compare phone numbers, names, and even resume content to catch variations.

Implement fuzzy matching for name variations as well. “Bob Smith” and “Robert Smith” might be the same person, and your system should flag potential matches for human review rather than automatically merging records.

Built-in OFCCP audit support throughout your deduplication process. You need complete visibility into which applications were merged, when, and by whom. This documentation becomes critical during compliance reviews and helps maintain accurate diversity reporting across all recruitment channels.

Diversity & Inclusion Technology Stack Integration

Bias Detection Tool Integration with Existing Recruitment Workflows

Your bias detection tools are only as effective as their level of integration within your existing workflows. Most organizations make the mistake of treating these systems as add-ons rather than core components of their recruitment architecture.

The key lies in real-time data flow between your bias detection platform and your ATS. When a recruiter reviews candidates in systems like Avionté, the bias alerts need to surface immediately within the same interface. This means API connections that push screening results, interview feedback, and hiring decision data to your bias detection tool within seconds, not hours.

Configure your integration to trigger bias analysis at three critical points: initial candidate screening, interview scoring, and final hiring recommendations. Each trigger should include contextual data (job requirements, interviewer profiles, historical hiring patterns) to ensure your bias detection algorithms have sufficient information for accurate analysis.

Don’t forget workflow interruption protocols. When bias indicators exceed your predetermined thresholds, your system should pause the recruitment process and require manager review before proceeding. This isn’t about slowing down hiring – it’s about preventing costly discrimination claims down the road.

Inclusive Sourcing Platform Connectivity and Data Synchronization

Your inclusive sourcing platforms need bidirectional data flow with your primary recruitment systems. Too many enterprises treat sourcing platforms as isolated tools, creating data silos that undermine their diversity efforts.

Start with candidate pipeline synchronization. When your inclusive sourcing platform identifies potential candidates, that data should automatically populate in your ATS candidate pool. Systems like ApplicantPro can handle this integration well, but you need to map data fields correctly to avoid information loss during transfer.

Source tracking becomes critical here. Your integration architecture must maintain a clear audit trail showing which candidates came from inclusive sourcing efforts versus traditional channels. This data feeds directly into your OFCCP compliance reporting and helps you measure the effectiveness of your diversity sourcing investments.

Set up automated candidate scoring that weights diversity sourcing positively while maintaining qualification standards. Your job multi-poster platform should sync with these scoring algorithms to ensure diverse candidate pools reach the right hiring managers at the right time.

Diversity Analytics Dashboard Integration with Enterprise Reporting

Your diversity analytics dashboard needs to be the single source of truth for all recruitment diversity metrics. This means connecting data streams from your ATS, HRIS, bias-detection tools, and inclusive-sourcing platforms into a single, comprehensive view.

Build your integration around three core data categories: pipeline diversity (application ratios by demographic), process diversity (interview-to-offer ratios), and outcome diversity (actual hiring results). Each category requires different API connections and data transformation rules.

Real-time reporting capabilities separate enterprise-grade systems from basic tools. Your dashboard should reflect hiring activity within 15 minutes of it happening in your primary systems. When a hiring manager in UKG makes an offer, your diversity metrics should update almost immediately.

Configure automated alerting for deviations in the diversity metric. If your hiring ratios fall below established benchmarks for any demographic group, your system should notify relevant stakeholders before the trend becomes a compliance issue. This proactive approach prevents problems rather than just reporting them after the fact.

Third-Party D&I Vendor API Management and Data Governance

Managing multiple D&I vendor APIs requires a centralized approach to avoid security vulnerabilities and data inconsistencies. Most enterprises underestimate the complexity of maintaining 5-10 different vendor integrations simultaneously.

Implement an API gateway specifically for your D&I vendor connections. This creates a single entry point for all external D&I tools to access your recruitment data, allowing you to enforce consistent security protocols and rate limiting across all vendors.

Data governance becomes non-negotiable when dealing with diversity and inclusion information. Your integration architecture must ensure that sensitive demographic data flows only to vendors with appropriate certifications and contractual protections. Create separate API endpoints for anonymized diversity analytics versus personally identifiable information.

Version control your vendor integrations carefully. D&I platforms frequently update their APIs to add new bias-detection capabilities or compliance features. Your Greenhouse integration might work perfectly today, but API changes next month could break your diversity reporting if you don’t have proper version management in place.

Establish data retention policies that align with OFCCP compliance requirements while respecting individual privacy rights. Your integration should automatically purge certain data types after specified periods while maintaining aggregate diversity metrics for compliance reporting. This balance requires careful architectural planning but protects your organization from both compliance violations and privacy breaches.

Data Governance and Quality Management in Recruitment Integration

Master Data Management for Candidate and Job Information

Your recruitment technology stack is only as strong as the data flowing through it. When candidate profiles exist in three different formats across your ATS, HRIS, and background check platform, you’re not just looking at inconsistency—you’re staring at compliance nightmares waiting to happen.

Master data management starts with establishing a single source of truth for core entities. Your candidate ID should mean the same thing whether it’s referenced in your job multi-poster platform or your onboarding system. But here’s where most organizations stumble: they try to force every system to use the same data structure instead of creating translation layers that preserve each system’s strengths.

Smart enterprises create canonical data models that serve as bridges. Your ATS might store candidate skills as free text, while your analytics platform needs structured competency codes. Rather than forcing one system to change, build middleware that translates between formats while maintaining data integrity.

Consider implementing data stewardship roles within your recruitment team. Someone needs to own data quality, and that someone should understand both the business context and technical implications. They’ll catch issues like duplicate candidate records before they corrupt your diversity reporting or create OFCCP audit headaches.

Data Lineage Tracking Across Integrated Recruitment Systems

When your diversity metrics don’t match between systems, panic sets in. Was it the integration that failed? Did someone manually update data in one place but not another? Without proper data lineage tracking, you’re playing detective with incomplete clues.

Data lineage documentation should map every transformation your recruitment data undergoes. When a candidate applies through your career site, that application travels through multiple systems—each potentially modifying, enriching, or filtering the data. Your job distribution software might add source-tracking codes, your ATS might standardize location formats, and your background check system might append verification flags.

Implement audit trails that capture not only what changed but also when and why. Modern integration platforms provide built-in lineage tracking, but you need to configure them properly. Tag each data transformation with business context: “Salary normalized for market comparison” tells a different story than “Salary field truncated due to character limits.”

Industries with complex compliance requirements particularly benefit from granular lineage tracking. Aerospace companies dealing with security clearance requirements need to trace candidate data through multiple verification systems while maintaining clear audit trails.

Quality Assurance Protocols for Cross-System Data Integrity

Data quality isn’t a one-time setup—it’s an ongoing discipline. Your integration architecture should include automated quality checks at every data handoff point. But don’t just validate formats; validate business logic too.

Start with basic validation rules: email addresses should contain “@” symbols, phone numbers should follow expected patterns, and dates should fall within reasonable ranges. Then layer on business-specific validations. A software engineer position probably shouldn’t require 20 years of experience with a technology that’s only existed for five years (yes, this happens more than you’d think).

Implement exception handling that doesn’t break your entire integration flow. When bad data hits your quality checks, quarantine it rather than failing the entire batch. Your recruitment team needs visibility into these quality issues, but they also need the good data to keep flowing.

Cross-reference validations between systems add another layer of protection. If your ATS shows a candidate as hired but your HRIS has no corresponding employee record, flag it immediately. These discrepancies often indicate integration failures or manual process breakdowns that could impact compliance reporting.

Regular data quality audits should compare the integration architectures of recruiting systems. Sample candidate records monthly and verify they match across platforms. Architecture companies often discover licensing credential discrepancies during these audits—information that’s critical for both compliance and candidate qualification.

Privacy and GDPR Compliance in Multi-System Recruitment Architecture

Privacy compliance becomes exponentially more complex when candidate data flows across multiple systems. You’re not just managing data within one platform—you’re orchestrating privacy controls across your entire enterprise recruitment technology stack.

Start by mapping data flows with privacy implications. When a candidate exercises their right to deletion, which systems need to purge their data? Your ATS is obvious, but what about the analytics warehouse that stores aggregated diversity metrics? Or the email marketing platform that captured their job alert preferences?

Implement privacy-by-design principles in your integration architecture. Data minimization should be baked into your integration logic—don’t sync candidates’ Social Security numbers to systems that only need contact information. Purpose limitation means your recruiting analytics platform shouldn’t receive data intended only for payroll processing.

OFCCP compliance systems require special attention to privacy controls. While you need to collect and store demographic information for compliance reporting, access to it should be strictly controlled and kept separate from hiring decision data. Your integration architecture should enforce this separation automatically rather than relying on human judgment.

Consider implementing privacy orchestration tools that can execute data subject requests across multiple systems simultaneously. When someone requests data deletion, you want confidence that their information is purged from every connected system, not just the ones you remember to check.

Agriculture companies with seasonal hiring patterns face unique privacy challenges—managing temporary worker data across multiple harvest cycles while respecting privacy rights requires careful architectural planning.

Implementation Roadmap and Change Management for Enterprise Integration

Phased Integration Approach for Minimal Business Disruption

Smart integration architecture recruiting requires a measured rollout strategy. You can’t flip a switch and expect your entire talent acquisition team to adapt overnight.

Start with a pilot program involving 10-15% of your recruiting volume. Choose your most technically savvy recruiters and focus on one core integration (typically your ATS-to-job multi-poster platform connection). This controlled environment lets you identify bottlenecks without impacting your entire hiring pipeline.

Phase two expands to department-level rollouts. Engineering teams often adapt faster than sales recruitment, so sequence accordingly. Each phase should run 4-6 weeks before moving forward. This timeline gives you real performance data while maintaining recruitment velocity.

The final phase tackles your most complex integration scenarios. This includes OFCCP compliance job posting workflows and multi-system data synchronization. By this point, your team has confidence in the new architecture and can troubleshoot issues independently.

Stakeholder Alignment Strategies for Cross-Functional Recruitment Teams

Integration success depends on getting everyone rowing in the same direction. But recruitment teams span multiple departments, each with different priorities and varying levels of technical comfort.

Create integration champions within each recruiting function. Your diversity recruiting specialist becomes the go-to person for diversity & inclusion job posting integrations. Your campus recruiter owns the seasonal hiring technology stack. This distributed ownership prevents bottlenecks and builds internal expertise.

Weekly alignment meetings during implementation keep everyone informed without creating meeting fatigue. Focus on wins, blockers, and upcoming changes. Most importantly, document everything. Your integration decisions today become institutional knowledge tomorrow.

Executive sponsorship matters more than you think. When your Chief People Officer publicly supports the integration project, adoption rates increase by 40-60%. Make sure leadership understands both the short-term disruption and long-term efficiency gains.

Testing and Validation Frameworks for Complex Integration Scenarios

Enterprise recruitment technology stacks involve dozens of moving parts. One misconfigured API endpoint can crash your entire job posting workflow during peak hiring season.

Build comprehensive test scenarios that mirror real-world usage patterns. Your testing framework should include candidate application flows, job posting distribution across multiple channels, and compliance reporting generation. Don’t just test the happy path (everything works perfectly). Test edge cases, such as duplicate candidate records and incomplete application data.

Automated testing becomes critical as your integrations grow more complex. Set up monitoring that alerts you when job postings fail to reach specific job board distribution channels or when candidate data doesn’t sync properly between systems.

User acceptance testing with actual recruiters catches issues your technical team might miss. A recruiter trying to post 20 jobs simultaneously will stress your system differently than your QA engineer testing one job at a time.

Performance Monitoring and Continuous Optimization Post-Implementation

Integration architecture isn’t a “set it and forget it” project. Your technology stack needs ongoing attention to maintain peak performance.

Establish baseline metrics before implementation begins. Track job posting speed, candidate application completion rates, and system uptime. These numbers become your benchmark for measuring integration success. Most organizations see a 25-35% improvement in posting efficiency after proper integration implementation.

Create dashboards that show real-time integration health. When your job distribution software experiences API throttling or your ATS connection drops, you want to know immediately, not when recruiters start complaining.

Schedule quarterly integration reviews with your technical team and key stakeholders. Technology vendors update their APIs, compliance requirements change, and your hiring volume fluctuates. What worked perfectly in Q1 might need adjustment by Q3.

Document performance improvements and share wins across your organization. When your integration architecture reduces time-to-fill by 3 days or increases the number of diverse candidate applications by 40%, that’s a success story worth celebrating.

Ready to transform your recruitment technology stack? Integration architecture might seem complex, but the right approach turns complexity into a competitive advantage. Start with a phased rollout, align your stakeholders, test thoroughly, and monitor continuously. Your future self (and your recruiting team) will thank you for the upfront investment in doing integration architecture right.