We design, build and run the cloud platforms, data systems and AI agents that growing companies and enterprises depend on, across AWS, Microsoft Azure, Google Cloud and the full Microsoft stack from Power Platform to Fabric.
Trusted by finance teams to replace manual work with systems that hold up.
No open-ended discovery phases. In four weeks you know exactly what you have, what it costs, what's at risk, and what we'll fix first. And you'll already have something working.
We map your systems, data sources, integrations, licenses and the manual work hiding between them.
We review security, access, reliability and cost against how your platforms should be set up.
Every recommendation comes with effort, cost and business impact, so you can decide in one meeting.
We ship the first quick win: an automation, a dashboard or a fix that removes a real pain point.
Most of our clients start with one problem and stay because the same team can handle the cloud, the data, the automation and the AI that sits on top.
We start with one workflow that costs you real hours, like invoice intake, ticket triage, contract review or research. We build an agent around it, connect it to your systems, and test it against your own historical cases before it touches live work.
Aging servers, sprawling accounts, or a new platform that has to be right the first time. We build landing zones with identity, networking, logging and cost tagging in place from day one, then migrate in planned waves with a rollback path at every step.
Most reporting problems are data problems. We consolidate your sources into one governed platform, define the metrics your leadership actually argues about, and ship dashboards that refresh on schedule and match the numbers finance reports.
Approvals buried in inboxes, data copied between systems, spreadsheets acting as databases. We replace them with workflows that are tracked, auditable and owned by IT, often in weeks rather than a full development cycle.
Cloud bills nobody can explain, apps nobody owns, data shared far too widely. We put identity controls, data policies, monitoring and chargeback in place, so growth in users and AI doesn't turn into risk or runaway spend.
After launch we stay on. A named engineer who knows your environment handles monitoring, patching, releases and support, and you get a monthly report covering health, usage, incidents and spend.
Microsoft is our deepest bench. Our team has administered large Power Platform tenants, built Fabric and Power BI estates for executive reporting, run clustered on-premises gateways that refresh overnight without fail, and set the policies that keep Copilot useful and its costs predictable.
Environment strategy, data policies and a working Center of Excellence, so hundreds of makers can build without creating risk. Then we build the apps and flows that matter most.
Rollouts that start with cleaning up data permissions, not handing out licenses. Custom agents in Copilot Studio, plus credit tracking so the costs never surprise finance.
Lakehouses and semantic models built once and reused everywhere. Clustered data gateways so refreshes don't fail overnight, and capacity tuned so reports stay fast at month-end.
Extensions, workflows and integrations for Customer Engagement and Finance & Operations, built so they survive the next platform update.
Landing zones, app modernization, and Azure OpenAI applications with private networking, content filtering and usage limits from day one.
Tenant governance, retention and sharing policies, storage management across sites, and intranets people actually use.
An Agent Pod is a set of AI agents that runs one business process end to end, inside your own cloud. We build it, supervise it and improve it every month. You pay a monthly fee per process, not by the hour.
Reads every invoice arriving in the shared AP mailbox, whether PDF, scan or email body.
Pulls vendor, invoice number, line items, tax and totals, and suggests the cost codes.
Checks each invoice against purchase orders and receipts in your ERP and flags any mismatch.
Sends exceptions to the right approver in Teams or Slack with the reason attached.
Posts approved entries and logs every decision for audit.
Your AP team stops keying data and spends its time on the exceptions that need judgment. The same pattern runs our other Pods:
Packaged engagements built on the problems we solve most often. Each comes with a defined deliverable, so you know what you're buying before you start.
See every AI dollar by team, tool and use case, including Copilot licenses, Azure OpenAI and Bedrock tokens, and Fabric capacity, with budgets and alerts set before the next invoice arrives.
One use case taken from idea to a production app your people use. It covers model selection, search over your own documents, testing against real questions, and access guardrails.
Consolidate your reporting onto Fabric, Snowflake, Databricks or BigQuery, with a governed semantic layer, cost forecasts and your top ten reports rebuilt on it.
A production-ready landing zone on AWS, Azure or Google Cloud, defined as code, followed by your first migration wave with a documented cutover and rollback plan.
We inventory every app and flow, set environment and data policies, onboard your makers, and give IT a dashboard of what's running and who owns it.
A standing team that takes your backlog of manual processes and moves one to production every sprint, with integrations into ServiceNow, Salesforce, SAP and Dynamics 365.
Clear commercials from the first conversation. No surprise change orders and no billable hours you can't trace back to work.
A focused review of one platform or problem.
Defined outcomes, delivered in short iterations.
We run and improve what we've built, or what you already have.
AI agents that run a business process, priced on agreed volumes.
Deal, fund and portfolio data, strict access control, audit trails, and reporting that stands up to auditors and regulators.
Billing and matter tracking, outside-spend visibility, and document-heavy workflows that eat billable time.
Protected data, compliant analytics, and AI that works within strict access boundaries.
Service desk automation, access requests, platform administration and the reporting IT leaders need to run at scale.
A first cloud set up properly, Microsoft 365 configured right, and automation that handles admin work before you need to hire for it.
Cloud platforms built for uptime, data pipelines for transactions and risk, and controls ready for security reviews.
The architect who scopes your project is the one who builds it. No hand-off to a junior bench after the contract is signed.
We work across AWS, Azure and Google Cloud and the leading AI models. We recommend what fits your business, not what earns us a rebate.
Security, access policies, cost controls and documentation ship with every solution. They are never a phase two.
Fixed-fee assessments, fixed-scope projects and per-process Agent Pods. You know the cost before the work starts.
License sprawl, unused seats and unmonitored credit consumption, and how to see all three on one page.
Read the note → CloudA practical comparison on data residency, model choice, networking and cost, written for business and IT leaders.
Read the note → DataGateways, credentials, capacity throttling and the monitoring that catches failures before your executives do.
Read the note →AWS, Microsoft Azure and Google Cloud, and models from Anthropic, OpenAI, Google and leading open-source providers. We'll often recommend staying on the cloud you already use. A second platform only makes sense when it solves a real problem.
No. We work with enterprises and with growing businesses. The approach scales from a single automation or dashboard to a full cloud, data and AI program, and every engagement starts with the same 30-day plan.
Agents run inside your own cloud tenant, using your existing identity and access controls. We don't move your data into our systems, and we configure the model provider so your data isn't used for training.
Yes. Most managed engagements start with an existing environment. We begin with an assessment, fix the urgent risks, document what's there, and then take over day-to-day operations.
Assessments usually start within two weeks of our first call. Tell us your timeline when you get in touch.
Tell us what you're working on. You'll hear back from an architect, not a sales rep, within one business day.