Databricks is a data and AI platform built on the lakehouse: open Delta Lake tables in your cloud storage, used for both analytics and AI.
Salesforce Select Partner · 20+ enterprise implementations · 15+ years of team experience
Databricks data and AI engineering on a lakehouse your teams can trust.
Our engineers build lakehouses on Delta Lake: ingestion and pipelines with Lakeflow, governance with Unity Catalog, SQL warehouses for analysts, AI agents on governed data, and zero copy with Salesforce Data 360.
See the pipeline
- 15+Years of team experience
- 20+Enterprise implementations
- 60 minFree Databricks data and AI engineering review, with a written plan
- 5.0/5Client satisfaction (CSAT)
Proven Success With
5.0/5 CSAT
New to Databricks data and AI engineering?
What is Databricks data and AI engineering?
Lakeflow ingests, transforms and orchestrates data. Unity Catalog governs tables, files, models and who can reach them.
Analysts query through Databricks SQL, and AI agents built with Agent Bricks work on the same governed data.
Where you start
Where are you with Databricks?
What state is your Databricks platform in today?
- Path 01Not set up yet
A new lakehouse
You have chosen Databricks, or are close to it, and want the workspace set up properly from the start.
- Unity Catalog from day one
- Layered catalogs and schemas agreed
- First source loaded end to end
- Path 02Running, but fragile
Pipelines that break
Notebooks run on schedules nobody owns, and failures show up in reports first.
- Jobs and notebooks inventoried
- Pipelines rebuilt with expectations
- Alerts sent to an owner
- Path 03Older workspace
Moving to Unity Catalog
Tables still sit in the legacy Hive metastore, with access set per workspace.
- Tables and grants mapped
- Upgrade done schema by schema
- Jobs repointed and tested
A governed lakehouse with owned pipelines, clear access and data ready for analytics and AI
What we do
What do Databricks consulting services include?
Eight areas. Most platforms need all of them at some depth.
Lakehouse design
Catalogs, schemas and Delta tables by layer and domain.
Lakeflow Connect
Managed connectors for databases and SaaS sources.
Pipelines
Lakeflow pipelines with data quality expectations.
Lakeflow Jobs
Schedules, retries, alerts and run history.
Unity Catalog
Grants, row filters, column masks and lineage.
Databricks SQL
SQL warehouses for analysts and BI tools.
AI agents
Agent Bricks agents, evaluated with MLflow.
Data 360 zero copy
Data shared both ways with Salesforce.
Lakeflow pipelines
What does a Databricks lakehouse pipeline look like?
A sample customer pipeline. Raw data lands, is cleaned in steps, and serves analysts, agents and Salesforce from the same governed tables.
Lakeflow pipeline
SourcesERP, product events, Salesforce
Lakeflow ConnectManaged ingestion
Raw tablesData as it arrived
Cleaned tablesExpectations checked
Business tablesCustomer and revenue views
Databricks SQLDashboards and BI tools
Agent BricksAgents on governed data
Data 360Zero copy with Salesforce
Lakeflow Jobs
One job runs the chain, retries failed steps and alerts the owner.
Expectations
Rules on each table drop, flag or stop bad rows, and the results are kept.
In Git
Pipelines and jobs deployed from a repository with Declarative Automation Bundles.
Unity Catalog
How does Unity Catalog govern a table?
One business table and the six rules we set on it. The same rules apply to files, models and functions.
Unity Catalog tableprod.customer.customer_360
- Owner
- Customer data team
- Access
- Read for analysts, write for the pipeline only
- Row filter
- Region users see their region
- Column masks
- Emailphonedate of birth
- Lineage
- PlanPhase inActivePhase outEnd of life
- Quality
Named owner
A group owns each catalog, schema and table.
Every access request and failure has someone to go to.
Grants to groups
Privileges granted to account groups synced from your identity provider.
Joiners and leavers change access in one place.
Row filters
A function limits rows by the user's group.
One table serves every region safely.
Column masks
Personal fields masked unless the user is in an allowed group.
Analysts work with the data without seeing what they do not need.
Lineage kept
Unity Catalog records which jobs and tables feed this one.
You can see what breaks before you change a source.
Quality checked
Pipeline expectations and their results kept with the table.
People can see whether today's data passed.
Databricks and Data 360
How does zero copy work between Databricks and Salesforce Data 360?
Salesforce describes Zero Copy with Databricks as bi-directional: Data Sharing makes Data 360 data available in Databricks, and Data Federation lets Data 360 use lakehouse tables. One sample round trip.
- Salesforce CRM
- Data 360
- Unity Catalog
- Lakeflow pipeline
- Marketing team
- Salesforce CRM to Data 360: Contacts and orders unified
- Data 360 to Unity Catalog: Profiles shared in, no copy
- Unity Catalog to Lakeflow pipeline: Joined with product usage
- Lakeflow pipeline to Unity Catalog: Writes a scored table
- Data 360 to Unity Catalog: Reads the table through federation
- Data 360 to Marketing team: Builds a segment on the score
- Marketing team to Data 360: Approves the segment
How it runs
How does a Databricks engagement run?
Five phases, run as parallel workstreams. Your written proposal states the scope and milestones.
Workstream
- 01Assess
- 02Design
- 03Build
- 04Prove
- 05Hand over
Platform
Pipelines
Governance
Analytics and AI
Data 360
People
Cost and timing
What it costs and how long it takes
The review is free
A 60-minute architecture review of your Databricks setup, with a written plan you keep.
A fixed-scope proposal first
Before any work starts you get a written proposal: a fixed-scope project with milestones, or a monthly plan. You approve it, or you do not.
Timing follows scope
How long it takes depends on what is in scope. The proposal states the milestones, so you see the timeline before you commit.
Client stories
Client work we have delivered
Real engagements, described by industry. Each story covers the starting position, what we built and how we delivered it, end to end.
NonprofitContribution Reporting the Board Can Trust for an Environmental NonprofitSalesforce for an Australian environmental nonprofit: 14 reports and KPI dashboards for financial, in-kind and volunteer contributions, and 553 historical records corrected and reimported.Salesforce Platform · Reports and Dashboards · Data Loader · FlowRead the story 
Financial ServicesSelf-Hosted AI Research Infrastructure Behind a Salesforce Deal EngineSelf-hosted AI agent infrastructure for a US private equity advisory firm: n8n workflows, PostgreSQL, web research and Google Drive mandate documents, deployed with Coolify and writing results back to Salesforce.n8n · PostgreSQL · Coolify · FirecrawlRead the story 
Financial ServicesAI Deal Matching That Screens Companies Against Every Investor MandateSales Cloud, Agentforce, Data 360 and Prompt Builder for a US private equity advisory firm: mandates, AI first-pass ranking, deep scoring with rationale, and deals created from approved matches.Sales Cloud · Agentforce · Data 360 · Prompt BuilderRead the story Client reviews
What clients say about working with our architects
See how teams describe working with SynconAI, from first scope to production delivery.
Salesforce Select Partner30+ Salesforce certificationsDelivery from Delaware & Sydney, worldwide
Simply Outstanding
“SynconAI Consulting are Simply the Best in the Business When it comes to Salesforce implementation and AI-powered solutions, SynconAI are in a league of their own. Their expertise, dedication, and ability to deliver results that truly move the needle sets them apart from every other consulting partner we've worked with. What they achieved with our Sales Cloud, Service Cloud, and custom Agentforce agent has completely transformed how we operate streamlining our pipelines and our customer service, and automating tasks that used to consume hours of our team's time. They don't just implement technology they transform businesses. If you want the best, you work with their team.”
Sales CloudService CloudAgentforce
Jack BennettConsumer Goods & Retail · United States
“I had a very urgent deadline for our project reporting to be delivered and needed to build the module, dashboard and output reports in Salesforce. SynconAI were very responsive - they met with me online, responded to my emails quickly and took calls - whatever was needed to progress the work quickly. We are thrilled with the outcome and will continue to work with SynconAI in the future to continue to build our Salesforce capability and platform.”
Sales CloudService CloudNonprofit Cloud
Salesforce Managed ServicesAustraliaSalesforce Verified
“The team at SynconAI were fantastic, and promptly delivered on each project. They were able to guide us through every stage and made sure we were satisfied with the outcomes on multiple scopes of work.”
Sales CloudSlackFlowAgentforceMuleSoft
ManufacturingAustraliaSalesforce Verified
“They have been great and helping us transform out business by bringing what I conceptualize to life. Great at translating process/workflow needs into a solution. Been a pleasure work with and they're a critical part of our team and will be instrumental into bringing about my vision.”
Sales CloudFinancial Services CloudArchitectureAI
Financial ServicesUnited StatesSalesforce Verified
“Working with SynconAI was a seamless and highly professional experience from start to finish. They took the time to deeply understand our business processes before designing and implementing a Salesforce solution tailored specifically to our operational needs. The team demonstrated strong technical expertise across Salesforce configuration, automation, integrations, reporting, and user experience design.”
SalesforceExperience CloudCustom DevelopmentAutomationReporting
Salesforce ImplementationSalesforce Verified
Frequently asked questions
Databricks data and AI engineering, answered.
Straight answers about the lakehouse, Lakeflow, Unity Catalog, AI agents and zero copy with Salesforce Data 360.
Designing and building a lakehouse on Databricks: Delta tables, Lakeflow ingestion and pipelines, Unity Catalog governance, SQL warehouses for analysts, AI agents on governed data and links to Salesforce.
Yes. Our engineers design and build Databricks platforms as a fixed-scope project or on a monthly plan. SynconAI is an independent consulting firm.
Yes. Our engineers can join your team for a build or a Unity Catalog upgrade, working in your repositories and to your standards, under a written proposal.
Databricks' data engineering suite: Lakeflow Connect for ingestion, Lakeflow pipelines built on Spark Declarative Pipelines for transformation, Lakeflow Jobs for orchestration, and Lakeflow Designer for visual building.
Delta Live Tables is now called Lakeflow pipelines. Databricks says no migration is required and existing pipeline code still works, with newer Python names recommended.
Databricks' governance layer for tables, files, models and functions. It holds grants, row filters, column masks, tags and lineage in one place across workspaces.
Through Zero Copy. Data 360 data can be shared into Unity Catalog, and Data 360 can read lakehouse tables through federation, without copying the data.
Yes. We build agents with Agent Bricks on governed data, trace and evaluate them with MLflow, and keep a person approving any action that changes a record.
Databricks, Unity Catalog, Lakeflow and Agent Bricks are trademarks of Databricks, Inc. Delta Lake, MLflow and Apache Spark are trademarks of their owners. Salesforce and Data 360 are trademarks of Salesforce, Inc. SynconAI is an independent consulting firm; apart from its Salesforce partner status, it is not affiliated with or endorsed by these companies.
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