Devsources delivers end-to-end technology services across artificial intelligence, data engineering, enterprise performance management, cloud platforms, automation, and custom application development — for federal agencies and private-sector organizations alike.
Most consultancies specialize in one lane, leaving clients to integrate three or four vendors and absorb the coordination risk themselves. We cover the full stack with one accountable team, backed by delivery experience inside environments where security and compliance requirements are non-negotiable.
Capabilities
Six practice areas, one delivery team. Each capability stands on its own — and they compound when combined on the same modernization program.
01
Focus
Custom model development
Intelligent automation
Production integration
Explainability and audit trails
Most AI initiatives stall in the same place: a promising proof of concept that never survives contact with real data, real users, and real compliance review. We build AI and machine learning systems designed for production from the first sprint — with the data pipelines, monitoring, and documentation the model needs to be trusted once it's live. That means starting with the decision you're trying to improve rather than the algorithm you'd like to use. If a well-instrumented rules engine solves the problem, we'll say so. When machine learning genuinely earns its place, we build it with the same rigor we'd apply to any other production system.
Where AI/ML delivers
Custom model development — models trained on your data and your problem, not a generic pre-built solution retrofitted to fit.
Intelligent automation — applying ML to processes that currently consume analyst hours on classification, extraction, and routing.
Production integration — connecting models to the systems where decisions actually get made, with the reliability those systems demand.
Explainability and audit trails — because in regulated environments, a prediction nobody can explain is a prediction nobody can use.
Why it works with our data practice
AI is only as good as the data underneath it. Because our data engineering and AI teams sit under the same roof, model work doesn't stall waiting on a separate vendor to fix a pipeline — the same team owns both ends of the problem.
02
Focus
Financial Planning
Workforce Planning
Implementation & rollout
Integration with data platforms
Oracle EPM Cloud is a specialized platform, and the talent to implement it well is genuinely hard to find. It's one of the clearest reasons clients choose Devsources: we bring enterprise finance fluency that most cloud and development shops simply can't claim, alongside the technical depth to integrate planning with the rest of your data estate. Financial planning and workforce planning aren't IT projects with a finance stakeholder attached — they're finance processes that happen to run on software. We approach them accordingly, working with the people who own the numbers rather than around them.
What we implement
Financial Planning — budgeting, forecasting, and scenario modeling built on Oracle EPM Cloud.
Workforce Planning — headcount, compensation, and capacity planning connected to the financial model.
Data integration — feeding EPM from source systems so planning runs on current numbers, not a monthly export.
Rollout and adoption — configuration and enablement so the platform survives the first planning cycle.
Finance fluency as a differentiator
Experience with Oracle EPM Cloud signals something broader: comfort operating inside enterprise finance and planning functions, where accuracy expectations are absolute and the audit trail matters as much as the output. That's a different discipline from standing up infrastructure — and it's one we've built deliberately.
03
Focus
Databricks
Tableau
Qlik
Power BI
Organizations rarely have a data shortage. They have a trust shortage — three systems reporting three different numbers, and no one certain which to bring into the room. Our data engineering practice exists to close that gap: reliable pipelines feeding analytics people are willing to act on. We build on Databricks for engineering and processing at scale, and deliver the output through whichever visualization layer your organization already lives in — Tableau, Qlik, or Power BI. The platform choice follows your team's reality, not our preference.
What we build
Data pipelines and platforms — ingestion, transformation, and processing architected on Databricks to handle production volume.
Analytics and dashboards — reporting in Tableau, Qlik, or Power BI, designed around the decisions they support.
Source system integration — consolidating fragmented systems into one dependable view.
Foundations for AI — the clean, governed data that machine learning work depends on.
Analytics that survive scrutiny
In federal and regulated environments, a dashboard is only useful if its numbers hold up when challenged. We build lineage and governance into the pipeline rather than bolting it on afterward — so when someone asks where a figure came from, there's an answer.
04
Focus
AWS
Microsoft Azure
Migration & modernization
Secure infrastructure
Cloud migration is where modernization programs most often lose their timeline — usually because security and compliance requirements arrive late, after architecture decisions have already been made. We work the other way around, treating those requirements as design inputs from the start. That habit comes from experience: delivering inside federal environments means the security posture isn't a phase near the end of the project. It's the constraint the architecture is built around.
Cloud engineering services
Migration — moving workloads to AWS or Azure with a plan for what gets rehosted, refactored, or retired.
Modernization — restructuring legacy applications to actually benefit from cloud rather than just relocate to it.
Secure infrastructure — environments built to meet compliance obligations from day one.
Platform foundations — the infrastructure your data, AI, and application workloads run on.
AWS and Azure
We work across both major platforms, which means the recommendation you get reflects your existing estate, licensing, and team skills — not a single-vendor allegiance.
05
Focus
Microsoft Power Platform
Appian
Workflow automation
Process digitization
Not every problem justifies a custom application. A large share of the manual work inside most organizations — approvals, intake forms, handoffs, status chasing — can be automated on a low-code platform in a fraction of the time and cost. Knowing which problems belong in which category is most of the value. We build on Microsoft Power Platform and Appian, and we'll tell you when a workflow deserves custom development instead. Low-code that's pushed past its limits becomes the technical debt you were trying to avoid.
Where low-code fits
Workflow automation — replacing email-and-spreadsheet processes with tracked, auditable workflows.
Process digitization — turning paper and manual steps into systems that report on themselves.
Internal tooling — the applications that are real work but never survive the roadmap prioritization.
Rapid delivery — solutions in weeks, so teams stop waiting on the development backlog.
Governed, not shadow IT
Low-code platforms spread quickly and, left ungoverned, become an unmanaged application estate nobody can audit. We implement them with the ownership, standards, and lifecycle discipline that regulated environments require.
06
Focus
Java
.NET
SharePoint
Test Automation — Selenium
When the requirement is genuinely specific to your organization, an off-the-shelf product won't cover it and low-code will buckle under it. That's where custom development earns its cost — and where the quality of the engineering determines whether you own an asset or inherit a liability. We build on Java, .NET, and SharePoint — enterprise stacks with long support horizons and deep talent pools, so the application stays maintainable long after the initial build team has moved on.
Development services
Custom applications — built on Java and .NET for requirements that off-the-shelf software can't meet.
SharePoint solutions — collaboration and content platforms configured and extended to fit real workflows.
Test automation — Selenium suites that make releases repeatable instead of nerve-racking.
Modernization — bringing legacy applications forward without a full rewrite where one isn't warranted.
Quality as a delivery requirement
Test automation isn't a line item we add if budget allows. In environments where a failed release has consequences beyond an inconvenient afternoon, automated testing is what makes frequent, confident deployment possible at all.
Approach
Accountability
One team owns the outcome
No seams between vendors to argue over. When something breaks at an integration point, the same team that built both sides fixes it.
Breadth
The full roadmap, not one lane
Cloud, data, AI, planning, low-code, and development under one roof — so the next phase doesn't require a new procurement cycle.
Readiness
Teams that know the terrain
Delivery inside federal environments means we scale up without a learning curve on onboarding, clearances, or compliance reporting.
Industries
FAQ
What digital transformation services does Devsources provide?
Six practice areas: AI and machine learning, Oracle EPM Cloud, data and analytics, cloud platforms, low-code and automation, and application development. In practice, they're delivered together — a cloud migration usually has a data component, and an AI initiative depends on the pipelines underneath it.
Do you work with federal agencies?
Yes. Federal delivery is a core part of our experience, including work with the World Bank, CBP, ICE, and DOW. That history means our teams are already familiar with the onboarding, clearance, and compliance reporting requirements federal work involves — so they scale up without a ramp-up period.
What makes your Oracle EPM Cloud practice different?
Oracle EPM Cloud expertise is genuinely scarce, and it signals something most technology vendors can't claim: fluency in enterprise finance and planning, not just IT infrastructure. We implement Financial Planning and Workforce Planning, and integrate them with the broader data estate so planning runs on current numbers.
Which cloud platforms do you work with?
AWS and Microsoft Azure. Working across both means our recommendation reflects your existing estate, licensing position, and team skills rather than a single-vendor allegiance.
Can you take on a single capability, or do we have to engage the whole stack?
Each capability stands on its own — plenty of engagements start with one. The advantage of the full stack is what happens next: when the program expands, the next phase doesn't require a new vendor search and a new procurement cycle.
What is Devsources' company background?
Devsources is a minority women-owned small business and a digital transformation partner serving federal agencies and private-sector organizations across cloud engineering, cybersecurity, application development, data engineering, and AI/ML. We also hold an enterprise partnership with HCL Tech.
Start a conversation
Send a note about the systems, data, or platforms you're working with — we'll come back with how Devsources would approach it.
A trusted digital transformation partner delivering secure, modern technology across cloud, data, AI/ML, and enterprise planning.
