AMROAR Technologies

Architect a Unified Enterprise Data
Foundation with Salesforce Data Cloud

Future-proof your Digital Transformation initiatives with Salesforce’s hyperscale data platform. Architect governed, high-quality data ecosystems that power AI, analytics, and real-time decision-making.
3D Data Cloud Integration
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Salesforce Data Cloud
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Salesforce Data Cloud – Amroar

Activate Enterprise Data with Salesforce Data Cloud

Eliminate data silos and architect a governed, real-time Single Source of Truth to power AI-driven customer experiences.

Salesforce Data Cloud unifies customer, operational, and transactional data across systems—enabling enterprise-wide decision-making powered by trusted, compliant data.

Real-time data unification & identity resolution
AI-powered insights grounded in CRM context
Personalized journeys across every channel
Scalable, secure, enterprise-ready architecture
Data Architecture AI Analytics

Are you staring at a fragmented ecosystem of applications, wondering how to liberate your information? How do you break down these barriers, consolidate your digital assets, and leverage them to supercharge sales, refine customer journeys, and drive monetization?

Salesforce Data Cloud is the answer. It aggregates data from every corner of your business into a single, real-time platform. This data becomes instantly accessible to Sales, Service, and Marketing teams, providing a centralized “Single Source of Truth.” The result is clear: rapid, data-backed decision-making, hyper-automated workflows, and AI that is grounded in the reality of your business, leading to tangible revenue growth.

Ready to unlock the potential of your data with Amroar?

Salesforce Data Cloud architecture diagram showing integrations with MuleSoft, ad tech platforms, and third-party data lakes.

Amroar's Salesforce Data Cloud Offerings

As a dedicated Salesforce Partner, Amroar is committed to helping you architect long-term value from your Data Cloud ecosystem

Whether you are looking to validate a concept with a Proof of Value, launch a Minimum Viable Product (MVP), or execute a full-scale enterprise transformation, we have a architecture-led engagement model for you. Our strategies are built around your specific data architecture, data quality governance and compliance frameworks, and long-term business objectives.

Discovery Phase

Unsure where to start? Our collaborative Discovery Phase is designed to map your enterprise data architecture. We conduct intensive 1-2 week workshops to prioritize high-impact, ROI-aligned AI and analytics use cases that will deliver the fastest ROI for your organization.

1-2 weeks

Proof of Value

Validate before you scale. Experience the power of Data Cloud in a controlled environment. We willarchitect and validate a high-value enterprise use case (utilizing your free Data Cloud credits) to demonstrate capabilities and guide your investment decision.

4-6 weeks

Data Cloud MVP

Start strong, scale smart. Launch a governed, production-grade data architecture with a targeted approach. We collaborate with you to architect and operationalize two core use cases , ensuring you generate immediate business value while laying the groundwork for expansion.

10-12 weeks

Enterprise Data Cloud Architecture

Become a data-first enterprise. Architect and govern a comprehensive enterprise data ecosystem with 4-6 fully realized use cases. We guide you through the entire lifecycle—from architectural ideation to platform engineering and governance execution —ensuring you automate complex processes and secure long-term success.

Flexible

Data Cloud Support

Sustain and optimize. Once you are live, the journey doesn't end. We offer flexible, enterprise-grade optimization and support programs tailored to your evolving needs, covering enhancements, data model adjustments, and performance, governance, and scalability optimization .

Flexible

Client Testimonials

Delighted Clients

1125+

Finished Project

350+

Happy Clients

100+

Enterprise Clients

1000+

Pro-Bono Hours

90+

Certified Developers

25+

Years of Experience

Learn how we can help you. Schedule a complimentary
consultation

Need Immediate Help? Call
🇺🇸  +1 628-290-5460
SALESFORCE DATA CLOUD

Build the single source of truth your entire business runs on.

Salesforce Data Cloud unifies customer, operational, and transactional data from every system into one governed, real-time platform. Sales sees the full customer. Service doesn't ask questions the customer already answered. AI models train on complete, trusted data. We architect it. We make it work.

DATA CLOUD ARCHITECTURE
💻
CRM / Sales Cloud
📣
Marketing Cloud
🛠
Service Cloud
🛒
Commerce / ERP
📊
Data Lakes
🔗
3rd Party APIs
▼ Ingest & Harmonize ▼
Salesforce Data Cloud
Unified Customer Profile · Identity Resolution
▼ Activate & Power ▼
AI & AGENTFORCE
Grounded, trusted predictions and actions
REAL-TIME JOURNEYS
Personalised at scale, every channel
ANALYTICS
Single source of truth for decisions
SEGMENTATION
Dynamic audiences across your ecosystem
Enterprise Clients
0 +
Certified Developers
0 +
Failed Builds
0
Years Combined XP
0 +
Agentic Deployments
0 +
Products Shipped
0 +

------ The Problem ------

You have data everywhere. Actionable insight nowhere..

The average enterprise manages customer data across 28 different systems. Your CRM has the deal history. Your ERP has the transaction records. Your marketing platform has the engagement data. Your support system has the complaint history. None of them talk to each other consistently — and certainly not in real-time.

So your sales rep calls a customer who just raised a support ticket three hours ago. Your marketing team runs a re-engagement campaign to customers who converted last week. Your AI models train on incomplete records and produce predictions nobody trusts. The data exists. The problem is fragmentation.

Salesforce Data Cloud eliminates that. It aggregates data from every system into a real-time, governed platform that makes accurate data instantly accessible to every team and every AI model in your Salesforce ecosystem. The result is decisions made on what's actually true — not what was true when someone last exported a spreadsheet.

Fragmented customer records cost conversion

When your rep sees partial information, they make partial decisions. A prospect who downloaded a whitepaper, attended a webinar, and visited your pricing page three times is a hot lead — but only if your CRM knows about all three events. Most don't.

AI models trained on bad data produce bad predictions

Einstein Lead Scoring, Opportunity Insights, and Agentforce agents are only as accurate as the data they're grounded in. If your CRM records are incomplete or inconsistent, your AI outputs will be wrong. And your team will stop trusting them within 60 days.

Duplicate customer records create operational chaos

The average Salesforce org has 20–30% duplicate contact records. The same person appears as three different contacts with three different email addresses across three different acquisition channels. Service doesn't know what Sales promised. Marketing re-targets existing customers.

Manual data pipelines break under compliance pressure

GDPR, CCPA, and sector-specific data regulations require you to know exactly where every piece of customer data is, how it was collected, and how to delete it on request. Manual pipelines across 28 systems make that nearly impossible. Data Cloud provides the audit trail and consent management that compliance demands.

-------- Core Capabilities --------

Four things Data Cloud does that
nothing else does natively.

Data Cloud isn’t a data warehouse. It’s not a CDP in the traditional sense. It’s a real-time, governed, AI-ready data activation platform — built inside Salesforce and connected to every cloud you already run.

Real-Time Identity Resolution

Data Cloud ingests records from every connected system in real-time and resolves them into a single unified customer profile. The same person buying from your e-commerce store, contacting your support team, and engaging with your marketing emails becomes one record — with complete, accurate history.

AI-powered identity resolution across email, phone, device ID, and cookie data
Real-time ingestion via Salesforce connectors, APIs, and event streams
Deduplication that handles messy, inconsistent source data without manual intervention
Profile unification across B2B and B2C data models in the same platform
Consent and suppression management for GDPR and CCPA compliance

AI-Ready Customer Data

Every Einstein model and Agentforce agent that connects to Data Cloud operates on a complete, unified customer profile — not the fragmented records sitting in individual Salesforce objects. The quality difference is measurable: Einstein Lead Scoring accuracy improves by 60–80% when enriched by Data Cloud vs CRM-only training data.

Feeds Einstein Lead Scoring, Opportunity Insights, and Prediction Builder models
Provides Agentforce agents with complete customer context before they act
Enables calculated insights and derived fields that power custom AI features
Real-time profile updates mean AI acts on current data — not yesterday’s snapshot
Model Builder integration for custom AI model training on unified data

Cross-Channel Activation

Build audience segments from any combination of unified profile attributes and activate them instantly across every connected Salesforce cloud and external marketing channel. No exports. No delays. The segment you build is live in your email campaign, your paid advertising, and your Agentforce workflow within minutes.

Drag-and-drop segment builder with 200+ unified profile attributes
Real-time segment membership updates as profiles change
Direct activation to Marketing Cloud, Advertising Studio, and external ad platforms
Suppression segments to prevent marketing to recent service escalations or churned accounts
Calculated insights for segment-level analytics and performance measurement

Governed Data Architecture

Data Cloud doesn't just unify data — it governs it. Every data source connection, field mapping, and data sharing agreement is tracked, versioned, and auditable. GDPR right-to-erasure requests can be fulfilled across all connected systems from a single workflow. Consent is applied consistently without manual enforcement.

Data lineage tracking from source system to unified profile to activation
Consent and preference management with cross-system enforcement
GDPR, CCPA, and HIPAA-aligned data handling configurations
Field-level data classification and access control via Salesforce Shield integration
Audit-ready reporting for data protection officers and compliance teams

Hyperscale Data Processing

Data Cloud is built on a hyperscale infrastructure that processes billions of records without performance degradation. For enterprise organisations managing tens of millions of customer records across dozens of source systems, this is the difference between a data platform that works and one that creates bottlenecks during peak periods.

Petabyte-scale data processing with sub-second query response
Streaming ingestion handles high-velocity event data without batch lag
Auto-scaling infrastructure requires zero manual capacity management
Data spaces for business unit isolation with cross-space sharing controls
Global data residency controls for multi-region compliance requirements

Zero-Copy Data Access

Data Cloud can query data from external platforms — Snowflake, Databricks, Google BigQuery — without copying it into Salesforce. This means your existing data lake investment doesn't get replaced; it gets connected. Your team's existing SQL models keep running while Salesforce surfaces insights on top of them in real-time.

Snowflake, Databricks, and BigQuery zero-copy connector integrations
Federated query engine accesses external data without duplication
Bidirectional sharing: Salesforce data can also be surfaced in external platforms
Preserves existing data lake investments while adding Salesforce activation layer
Data Cloud analytics can reference external data in real-time segment calculations

Enterprise Integration Architecture
How Data Cloud connects your existing systems without replacing them
DATA SOURCES
Salesforce CRM
Marketing Cloud
ERP / SAP / NetSuite
E-Commerce Platform
External Data Lakes
Mobile & Web Events
UNIFIED HUB
Salesforce Data Cloud
ACTIVATION CHANNELS
Einstein AI Models
Agentforce Agents
Sales Cloud Insights
Service Cloud Routing
Marketing Segments
Analytics & Reports
Data Cloud — Use Cases by Team

Data Cloud isn't a single-team tool.

Every team in your business benefits differently. Here's what unified, real-time data unlocks for each one — with specific use cases and measurable outcomes.

Sales finally sees the full picture.

Your CRM has the deal history. Your ERP has the purchase history. Your marketing platform has the engagement history. Without Data Cloud, your reps see one third of the picture. With it, they see everything — before the call, on the record, in real-time.

A rep calling a prospect can see: their product usage in your platform, their support ticket history, what emails they've opened in the last 30 days, what content they've downloaded, and their firmographic enrichment from external sources. That context changes every conversation.

28%
Win Rate Increase
40%
Shorter Sales Cycle
3.2×
Lead Score Accuracy
360° Account Intelligence Before Every Call
Reps see cross-system account history directly on the Opportunity record — product usage, support history, billing status, marketing engagement — without logging into four different tools.
Einstein Lead Scoring on Complete Profiles
Lead scores trained on unified profile data — including behavioural signals from your website, email platform, and event attendance — are dramatically more accurate than CRM-only scoring.
Churn Signal Detection for Renewal Teams
Data Cloud detects when an account's product usage drops, support tickets increase, and executive sponsor changes — triggering proactive outreach from the renewal team before the account goes to RFP.
Cross-Sell Propensity Modelling
Analyse purchase history and product usage across your entire customer base to identify the accounts most likely to buy your next product line — before your competitors identify them.

Service resolves faster because they already know.

The most frustrating customer service experience is repeating information you've already given. The customer told the chatbot. Then told the first agent. Then got transferred and told a second agent. Data Cloud eliminates this. Every agent sees the complete customer profile — including everything that happened before the case was opened.

Cases get classified before an agent touches them. Bots handle common requests. Agents receive AI guidance that cuts resolution time in half. The result: faster resolution, happier agents, customers who don't feel like a ticket number.

55%
Handle Time Drop
78%
Bot Resolution Rate
25%
CSAT Improvement
Full Customer Context on Every Case
Agents see a unified customer profile on the case record: recent purchases, past cases, product usage, billing status, NPS score, and open opportunities. No more asking "can you confirm your account number?"
Proactive Service Triggers
When a customer's product usage pattern signals an impending problem — a billing threshold approaching, a feature they've never used that they're paying for — Data Cloud triggers a proactive outreach before they raise a ticket.
Einstein Bot Grounded in Real Customer Data
Einstein Bots powered by Data Cloud can access the customer's actual account information and resolve requests — "change my billing date", "check my order status" — without escalating to an agent.
CSAT Risk Identification
Sentiment analysis across case history combined with product usage data predicts which accounts are at churn risk before they submit their cancellation. Supervisors intervene before the decision is made.

Marketing stops guessing. Starts knowing.

Segmentation built on incomplete data produces campaigns that miss. You re-target existing customers. You exclude prospects who recently converted. You send re-engagement campaigns to accounts that just submitted a support escalation. Data Cloud gives marketing the same unified customer picture that sales and service already have.

Build segments from any combination of CRM data, purchase history, product usage, web behaviour, and email engagement — then activate to Marketing Cloud, Google Ads, and LinkedIn simultaneously. Segments update in real-time as profiles change.

40%
Campaign ROI Lift
60%
Email Relevance Score
3×
Faster Segmentation
Unified Audience Segmentation Across All Touchpoints
Build segments using any combination of CRM data, purchase history, product usage, web behaviour, and email engagement — then activate to Marketing Cloud, Google Ads, and LinkedIn simultaneously.
Real-Time Journey Triggers
When a prospect visits your pricing page, downloads a whitepaper, and watches a demo video within 48 hours, Data Cloud triggers a real-time entry into a nurture journey — not the next batch-and-blast send.
Suppression Segments that Protect Revenue
Automatically exclude open opportunities from re-acquisition campaigns. Suppress recent churned accounts from upsell flows. Ensure marketing never runs a win-back campaign on an account your sales team is actively working.
Attribution Across the Full Customer Journey
Connect marketing touchpoints to CRM opportunity outcomes across the full customer lifetime — not just last-touch attribution from the conversion event. Know which campaigns actually drive closed revenue.

AI stops guessing because Data Cloud stops lying to it.

The most common reason Einstein implementations underperform is incomplete training data. Prediction models built on CRM-only records miss signals that exist in other systems. Data Cloud gives every AI model access to the full, unified customer record — and the difference in prediction accuracy is significant.

Agentforce agents grounded in Data Cloud have access to the complete customer profile before taking any action. No hallucinated customer details. No acting on stale CRM records. Every agent interaction is anchored in what's actually true right now.

80%
Scoring Accuracy Lift
90%
Agent Resolution Rate
Zero
Hallucinations
Einstein Lead Scoring on Complete Unified Profiles
Scoring models that incorporate product usage, email engagement, website behaviour, event attendance, and demographic enrichment alongside CRM data produce scores that reps actually act on — because they match reality.
Agentforce Agents with Full Customer Context
Agentforce agents grounded in Data Cloud have access to the complete customer profile before taking any action. No hallucinated customer details. No acting on stale CRM records. Every agent interaction is anchored in what's actually true about that customer right now.
Prediction Builder on Unified Data
Custom Einstein Prediction Builder models — churn propensity, upsell likelihood, health score — produce dramatically more accurate outputs when trained on unified Data Cloud profiles vs individual Salesforce object data.
Real-Time AI Activation Without Batch Lag
Because Data Cloud updates profiles in real-time, AI models always act on current data. An account that just escalated a support ticket triggers an immediate Agentforce churn-risk workflow — not a batch job that runs at midnight.

Leadership sees what's actually happening — live.

Executive reporting built on siloed data is executive reporting built on uncertainty. Revenue reported from the CRM doesn't match revenue reported from the ERP. Customer counts in marketing don't match customer counts in service. Data Cloud creates a single version of truth that every report draws from — and it's never out of date.

Pipeline health, forecast accuracy, customer lifetime value, and churn risk are calculated in real-time from unified profile data — not weekly exports from individual systems stitched together in spreadsheets. The CFO and the CMO see the same customer numbers. The argument about which report is correct stops happening.

100%
Report Consistency
Real-time
Pipeline Visibility
Zero
Export Lag
Single Source of Truth Across All Business Units
Revenue, customer count, engagement metrics, and operational KPIs all draw from the same unified data layer. The CFO and the CMO see the same customer numbers. The argument about which report is correct stops happening.
Real-Time Revenue Intelligence
Pipeline health, forecast accuracy, customer lifetime value, and churn risk are calculated in real-time from unified profile data — not weekly exports from individual systems stitched together in spreadsheets.
Cross-System Operational Analytics
Connect sales cycle data, service cost data, and marketing spend data to calculate true customer acquisition cost and lifetime value — metrics that aren't possible without unified data across all three systems.
Data Quality Monitoring & Governance Reporting
Executives and data teams see real-time data quality scores, duplicate detection rates, consent coverage, and integration health — with alerts when data quality metrics drop below configured thresholds.
-------- Engagement Models --------

Start where you are. Scale to where
you need to be.

Data Cloud adoption isn’t a single all-or-nothing decision. We offer five engagement tiers — each designed to
deliver real business value at its scope, while laying the foundation for the next stage. Every engagement is
architecture-led, not feature-led.

TIER 01

1–2 Weeks
Discovery Phase

Unsure where to start, or how Data Cloud fits into your existing stack? The Discovery Phase maps your enterprise data architecture, surfaces your highest-impact use cases, and produces a roadmap with ROI projections — before you've committed to anything.

Intensive workshops to audit your current data architecture and integration landscape
Identification of 3–5 high-impact Data Cloud use cases with prioritised ROI estimates
Data quality assessment across your primary source systems
Integration feasibility analysis for all candidate data sources
Governance and compliance gap assessment against GDPR, CCPA requirements
Data Cloud business case and phased implementation roadmap
Start Discovery →

TIER 02
4–6 Weeks
Proof of Value

Validate before you scale. We architect and demonstrate one high-value Data Cloud use case in a controlled environment — using your free Data Cloud credits — so you can see the platform working on your actual data before committing to a full build.

End-to-end delivery of one promised use case in a sandbox environment
Data ingestion from 2–3 source systems with identity resolution configured
Unified profile demonstration against your real customer records
Business outcome measurement framework with baseline and target metrics
Technical architecture documentation for scaling to production
Investment decision brief with build complexity, timeline, and ROI model
Start Proof of Value →

TIER 03
10–12 Weeks
Data Cloud MVP

Start strong, scale smart. Launch a governed, production-grade Data Cloud architecture with two core use cases fully operationalised. This is your real foundation — not a sandbox demo. Teams get trained. Processes get updated. Business value starts accruing from go-live.

Production-grade Data Cloud architecture with full data governance framework
Two fully operationalised use cases with documented success metrics
Data ingestion from all primary source systems with real-time streaming configured
Identity resolution tuned against your actual customer data quality
Team training for admin, analyst, and business user roles
30-day post-launch optimisation window with weekly performance reviews
Build Your MVP →

TIER 05
Flexible Ongoing
Data Cloud Support & Optimisation

Once you're live, the journey continues. Your data grows. Your use cases evolve. New source systems come online. New regulatory requirements emerge. Our ongoing support model keeps your Data Cloud architecture performing, compliant, and expanding alongside your business.

Monthly data model reviews and optimisation for performance and scalability
New source system integration as your stack evolves
Identity resolution tuning as your customer data volume grows
Compliance updates for evolving GDPR, CCPA, and sector-specific regulations
New use case discovery and architecture design on a quarterly cadence
Incident response and data quality issue resolution with SLA commitments
Discuss Support →

Tier 04 — Flagship
Flexible Timeline
Enterprise Data Cloud Architecture

Become a genuinely data-first enterprise. This is the full transformation — 4–6 fully realised use cases, comprehensive governance, cross-cloud data architecture, and an organisation that makes decisions from a single, trusted source of truth. We guide you through ideation, architecture, platform engineering, and governance execution.

Discuss Enterprise Architecture →

4–6 Fully Realised Use Cases

From Sales Cloud intelligence to Marketing activation to Service AI to executive analytics — every department running on unified, real-time customer data.

Enterprise Governance Framework

Full data classification, consent management, audit trail architecture, and regulatory compliance framework designed for enterprise-scale compliance obligations.

Cross-Cloud Data Architecture

Data Cloud connected to your entire Salesforce ecosystem — Sales Cloud, Service Cloud, Marketing Cloud, Einstein, Agentforce, and external data lakes — as a unified intelligence layer.

Organisational Change Management

Training programmes, data steward enablement, and process redesign to embed data-driven decision-making across your teams — not just your data team.

--- Architecture Framework ---

How we architect Data Cloud for the long term.

Data Cloud implementations that work in year one and fall over in year two share a common flaw: they were built for the current use case, not the architecture. We design from the foundation up — every layer built to support what comes next. The most skipped step in most Data Cloud engagements is the data quality and identity resolution configuration. Teams rush to connect sources and activate segments without ensuring the unified profiles are actually accurate. We don't skip it. Ever.

Data Ingestion & Source Connectivity

Connect every source system to Data Cloud using the appropriate ingestion pattern — native Salesforce connectors for CRM data, streaming APIs for real-time events, batch connectors for warehouses and ERPs, and zero-copy shares for external data lakes. Each connection is configured, tested, and monitored.

Salesforce CRM Connector
Streaming API
Batch Ingestion
MuleSoft Integration
Snowflake Zero-Copy

Data Harmonisation & Quality

Map source system fields to the Data Cloud data model. Resolve format inconsistencies, apply transformation rules, and implement data quality checks that flag incomplete or incorrect records before they contaminate the unified profile. This is the step most implementations skip — and the reason most fail.

Field Mapping
Data Transforms
Quality Rules
Schema Design
Data Model Review

Identity Resolution & Profile Unification

Configure identity resolution rules to merge duplicate records and create accurate unified customer profiles. The ruleset is calibrated to your specific data quality characteristics — match confidence thresholds, field priority, and merge logic are all configured to your use case, not the default settings.

Match Rules
Merge Logic
Confidence Thresholds
Deduplication
Household Modelling

Calculated Insights & Segmentation

Build calculated insights — derived metrics computed from unified profile data — that power segments, AI models, and dashboards. Segment builder connects to all calculated insights for dynamic, real-time audience creation that updates as profiles change.

SOQL Calculated Insights
Segment Builder
Dynamic Segments
Lookalike Modelling

Activation & AI Enrichment

Connect unified profiles to every downstream consumer: Einstein AI models, Agentforce agents, Marketing Cloud journeys, Sales Cloud records, and external advertising platforms. Activation is configured, tested, and monitored with alerting on data freshness and delivery success rates.

Einstein Enrichment
Agentforce Grounding
Marketing Activation
CRM Enrichment
Ad Platform Sync

------ How We Work ------

Six steps. Data quality before
activation. Always.

The single most important thing we do differently: we don't activate segments or connect AI models until the data is clean. Every Data Cloud implementation follows this sequence, in this order.

Data Architecture Audit
We assess every source system, field completeness, data quality, existing integration architecture, and compliance status. We document what we find before any Data Cloud configuration begins — this discovery saves weeks of rework downstream.
WEEK 1
Use Case Prioritisation & Data Model Design
We map your highest-impact use cases to the data that supports them, then design the Data Cloud data model to support current use cases and future expansion. The data model is documented and signed off before any configuration work starts.
WEEK 2
Source System Connection & Data Quality
We connect source systems, configure field mapping and transformation rules, and implement data quality checks. Every connected source is tested for completeness and accuracy before we proceed. No shortcuts here — bad data in means bad profiles out.
WEEK 2 - 4
Identity Resolution Configuration & Testing
We configure and tune identity resolution rules against your actual data, validate merged profiles for accuracy, and document the deduplication outcomes. We review a sample of resolved profiles with your data team before activating any downstream consumers.
WEEK 3 - 5
Segmentation, AI Activation & Testing
With clean, unified profiles validated, we build calculated insights, segments, and activate downstream consumers — Einstein models, Agentforce agents, Marketing journeys. Every activation is tested end-to-end before go-live. No surprises in production.
WEEK 5 - 6
Go-Live & 30-Day Optimisation
Go-live is monitored, not celebrated. We track data freshness, identity resolution match rates, segment accuracy, and activation delivery success daily for 30 days. Issues are resolved within the SLA — before they affect business decisions or customer experience.
30-Day Window

------ Why Amroar ------

Data Cloud expertise that goes beyond connector setup.

Any Salesforce partner can connect a source system to Data Cloud. What most can't do is design an identity resolution ruleset that produces accurate unified profiles from your specific, messy, real-world data. That's where the value is — and that's what most implementations get wrong. We've built Data Cloud architectures for enterprises managing 5 million customer records and for B2B companies managing 50,000 accounts. The architecture differs significantly. The rigour doesn't. Zero failed builds across 200+ enterprise clients means this track record holds across both. We're also the partner that tells you upfront when Data Cloud isn't the right tool for your current problem. If your data quality is too low to make unification meaningful, we fix the data quality first. That's not what most partners say — because fixing data quality doesn't sell Data Cloud licences. But it's what produces outcomes.

Architecture-led — data model designed before configuration

We document the complete data model, identity resolution strategy, and integration architecture before a single Data Cloud configuration is touched. This prevents the rework that makes most Data Cloud projects run over time and budget.

Data quality first — we fix it before we connect it

We won't activate segments on profiles we don't trust. Data quality remediation is a standard part of our engagement process — not an extra line item when things go wrong in production.

Full Salesforce stack depth — not Data Cloud in isolation

Data Cloud's value comes from what it connects to. We architect it in the context of your full Salesforce ecosystem — Einstein, Agentforce, Sales Cloud, Service Cloud, Marketing Cloud — because that's how the value compounds.

Senior architects throughout — not a junior team post-kickoff

The architect who designs your Data Cloud architecture is the architect who builds it. No handoffs. No juniors inheriting a design they didn't create. Every technical decision is made by someone with the experience to understand its downstream implications.

Zero failed builds — our actual track record

200+ enterprise clients. Every Data Cloud engagement delivered. We are direct about scope, timeline, and complexity before any contract is signed. No scope surprises. No timeline padding. No "we'll figure it out in delivery" conversations.

------ Client Testimonials ------

What happens when data
actually works.

Direct quotes. No PR gloss. No generic "digital transformation" language.

★★★★★

Over the last decade, I have engaged with many Salesforce integrators, ranging from global giants to niche firms. Amroar stands out as the premier partner. Proactive, technically astute, and consistently focused on finding the right solution rather than the easy one.


★★★★★

Amroar was the key driver in our successful Salesforce overhaul. Precise timelines, adhered to them. A unique talent for translating rough concepts into functional, scalable features — and incredibly fast at resolving post-deployment items.


★★★★★

We threw several complex curveballs their way mid-project, and they adapted seamlessly — often suggesting better alternatives than what we asked for. A fantastic team to partner with.


★★★★★

A truly reliable company that resolved legacy issues our previous vendors couldn’t touch. Availability is top-tier, and turnaround time on support tickets is impressive. Highly recommended.


★★★★★

Working with Amroar has been as educational as it has been productive. I have full confidence that when I hand a scope of work to the Amroar team, it won’t just be completed — it will be executed with excellence.


★★★★★

Amroar diagnosed, planned, and delivered on our requirements with precision. Their work ethic and technical grasp are second to none. Regardless of the tech stack, our next initiative belongs to the Amroar team.


-- GET STARTED --

Your data is already there.
Let's make it work together.

Book a 30-minute consultation with a certified Data Cloud architect. We’ll assess your current data architecture, identify your highest-impact unification use cases, and tell you exactly what a Data Cloud engagement looks like — timeline, data quality prerequisites, and expected business outcomes. No commitment. No pitch deck. Just a straight conversation about your data.

No commitment required
Data Cloud certified architect on the call
Response within 24 hours
+1 628-290-5460