Platform Architecture

The Platform Architecture Behind Your Intelligence Layer

CRED is built for enterprise scale—200+ integrations, predictive models, institutional memory, and continuous learning. Here's how it works under the hood.

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One platform. Four layers. Infinite intelligence.

Layer 01

Data Foundation

200+ integrations unifying external and internal data sources

Layer 02

Intelligence Engine

Predictive scoring, pattern recognition, institutional memory

Layer 03

Automation Layer

Workflows, AI agents, and the Action Marketplace

Layer 04

Interface Layer

Conversational AI, memory query, universal context

Intelligence that compounds with every decision

CRED gets smarter with every signal, decision, and result—turning today's work into tomorrow's competitive advantage.

Step 01

Capture Signals

Unify internal systems, external market data, and everyday interactions into a single intelligence foundation.

Internal systems: CRM, product usage, support tickets, HRIS, finance, sales calls, email

External signals: Market moves, competitor activity, intent data, pricing shifts, hiring trends, news

Interactions: Meetings, email, notes, documents, workflows, decisions

→

Step 02

Score + Recommend Actions

Generate predictive scores and recommended actions that teams can act on immediately.

Explainable scoring: Tied to your business logic

Configurable triggers: Playbooks by team

Delivered in context: Tools people already use

Confidence scores: For every prediction

→

Step 03

Learn From Outcomes

Close the loop by feeding results back into the intelligence layer—so scoring and recommendations improve over time.

Outcome tracking: What happened after the action was taken

Team feedback: Approve, adjust, or override recommendations

Performance data: Real results drive model improvement

Pattern evolution: Models adapt as your business changes

The Compounding Effect

Month 1–3

Baseline intelligence with external data + basic patterns

Month 4–6

Models calibrated to your organization's unique patterns

Month 7–12

Predictive accuracy significantly higher than generic models

Year 2+

Organizational intelligence becomes nearly impossible to replicate

Your Competitive Moat

Unlike traditional software that requires constant maintenance, CRED becomes more accurate and more specific to your organization with every decision tracked. The longer you use CRED, the harder it is for competitors to replicate your intelligence advantage. Your institutional memory becomes your moat.

200+ integrations. Real-time sync. One source of truth.

Customer Relationship Management

Salesforce, HubSpot, Microsoft Dynamics, Pipedrive, Copper

Human Resources & Talent

Workday, BambooHR, Greenhouse, Lever, ADP, Gusto

Marketing & Advertising

Marketo, Pardot, Google Ads, LinkedIn Ads, 6sense

Product & Analytics

Segment, Mixpanel, Amplitude, Heap, Google Analytics

Communication & Collaboration

Gmail, Outlook, Slack, Microsoft Teams, Zoom, Calendar

Finance & Operations

NetSuite, QuickBooks, Stripe, Bill.com

Market Intelligence

ZoomInfo, Clearbit, BuiltWith, Crunchbase, PitchBook

Custom Data Sources

REST APIs, webhooks, Snowflake, BigQuery, Redshift

Customer Relationship Management

Salesforce, HubSpot, Microsoft Dynamics, Pipedrive, Copper

Bidirectional sync, custom field mapping, real-time updates

Ingestion

Real-time streaming for time-sensitive data
Batch processing for historical data
Change data capture (CDC) for incremental updates

Enrichment

Automatic data enrichment from external sources
Entity resolution and deduplication
Data quality scoring and validation

Storage

Encrypted at rest and in transit
Data residency options (US, EU, custom)
Audit logs for all data access

The brain that never forgets

Predictive Scoring

How It Works

01Define what you want to score (leads, accounts, candidates, partnerships)

02Select features that matter to your business (company size, intent signals, engagement)

03Train models on your historical outcomes (won deals, successful hires, retained accounts)

04Deploy scores across your tools (CRM, ATS, email, dashboards)

05Models improve automatically as new outcomes are recorded

Model Types

Classification

Yes/no predictions

Regression

Numeric scores 0–100

Time-to-event

When will something happen

Ranking

Prioritize a list

How the brain gets fed—automatically

Meeting Intelligence

Automatic Capture

AI joins every scheduled call (Zoom, Teams, Google Meet)

Real-time transcription with speaker identification

Automatic summary generation

Action item extraction

Decision point identification

Sentiment analysis

Intelligence Extraction

Key insights summarized

Follow-up tasks assigned

CRM fields auto-populated

Relationship signals detected

Competitive intel flagged

Risk signals surfaced

From intelligence to automated outcomes

Pre-built Workflows

Ready Now

Designed by CRED's outcome engineering team based on common use cases across customers. Configurable to your specific business logic. Deploy in minutes, not months.

Custom Outcomes

Tailored

Built in collaboration with your team. Leverage your unique data and scoring models. Productized so other teams can reuse. Continuous improvement based on results.

Outcome Types

Workflows

Multi-step processes with conditional logic

Integrations across your entire stack

Human-in-the-loop for critical decisions

Automatic retry and error handling

AI Agents

Autonomous agents that execute complex tasks

Natural language task definitions

Learning from outcomes to improve over time

Guardrails and approval workflows for safety

Reports & Dashboards

Automated analysis and insights

Scheduled delivery to stakeholders

Custom metrics and KPIs

Drill-down capabilities for investigation

Outcome Monitoring

Real-Time Tracking

Every outcome execution logged

Success/failure rates monitored

Performance metrics tracked

ROI calculated automatically

Continuous Improvement

A/B testing different outcome configurations

Model retraining based on results

User feedback incorporated

Best practices shared across teams

Built for Fortune 500 scale and security

Certifications

SOC 2 Type II

GDPR compliant

HIPAA available for healthcare customers

Data Protection

Encryption at rest (AES-256)

Encryption in transit (TLS 1.3)

Key management with rotation

Data residency options (US, EU, custom)

Access Controls

Role-based access control (RBAC)

Single sign-on (SSO) via SAML 2.0

Multi-factor authentication (MFA)

Audit logs for all access and changes

Monitoring

24/7 security operations center

Intrusion detection and prevention

Vulnerability scanning and patching

Incident response procedures

Uptime SLA

99.9%

Query response time

<1s

High availability

Multi-region

Elastic infrastructure

Auto-scaling

Deployment Options

Cloud (Standard)

Fully managed by CRED

Multi-tenant with data isolation

Fastest time to value

Automatic updates and maintenance

Enterprise

Private Cloud (Enterprise)

Dedicated infrastructure for your organization

Enhanced security and compliance options

Custom SLAs and support

Your cloud account (AWS, GCP, Azure)

Select

On-Premises (Select)

Deployed in your data centers

Complete control over infrastructure

Air-gapped options available

White-glove deployment and support

Built to integrate with your stack

REST API

Complete programmatic access to CRED

Comprehensive documentation

SDKs for Python, JavaScript, Java

Webhooks for real-time events

Rate limiting and throttling

GraphQL API

Flexible querying for custom integrations

Efficient data fetching

Real-time subscriptions

Type-safe schema

Integration Patterns

Bidirectional Sync

Changes in CRED update your systems

Changes in your systems update CRED

Conflict resolution strategies

Automatic retry on failures

Event-Driven

Webhooks for real-time notifications

Event streaming to data warehouses

Trigger CRED workflows from external events

Batch Processing

Scheduled data imports/exports

Bulk operations for large datasets

CSV and file-based transfers

Developer Resources

Documentation

API reference

Integration guides

Code examples

Best practices

Support

Technical account manager

Developer Slack channel

Office hours and training

Custom integration consulting

From contract to value in 90 days

Phase 1Weeks 1–2

Discovery

Technical requirements gathering

Data source identification

Security and compliance review

Integration planning

Phase 2Weeks 3–4

Data Integration

Connect data sources

Data quality validation

Field mapping and enrichment

Historical data migration

Phase 3Weeks 5–8

Intelligence Configuration

Custom scoring model development

Pattern recognition setup

Institutional memory structure

Conversational AI activation

Phase 4Weeks 9–12

Outcome Deployment

Action Marketplace configuration

Workflow setup and testing

User training and onboarding

Go-live and monitoring

Support Tiers

Standard

Email and chat support

24-hour response time

Knowledge base access

Quarterly business reviews

Premium

Recommended

24/7 phone and email support

4-hour response for critical issues

Dedicated customer success manager

Monthly business reviews

Custom training programs

Enterprise

24/7 white-glove support

1-hour response for critical issues

Technical account manager

On-site support available

Architecture reviews and optimization

Executive business reviews

Ready to see the platform in action?

Schedule a technical deep dive with our platform architects. We'll walk through the architecture, discuss your specific use cases, and show you how CRED can become your intelligence layer.

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