--- title: Company — Matter + Energy | Who We Are description: Problem-solvers with deep experience in ITFM, AI research, and enterprise technology, taking on challenges that don't fit a standard template. image: https://www.matternenergy.com/hubfs/matter-energy/og-default.jpg --- [![Matter + Energy home](https://www.matternenergy.com/hs-fs/hubfs/matter-energy/logo/me-logo-horizontal.png?width=273&height=32&name=me-logo-horizontal.png)](https://www.matternenergy.com/) - [Home ▾](https://www.matternenergy.com/) [Who we are](https://www.matternenergy.com/company) [Technology Ecosystem](https://www.matternenergy.com/technology-ecosystem) [Teaming & Partnerships](https://www.matternenergy.com/teaming) - Solutions ▾ [Overview](https://www.matternenergy.com/solutions) [Technology Value Management](https://www.matternenergy.com/it-financial-management) [AI Adoption & Productivity](https://www.matternenergy.com/solutions/ai-adoption-productivity) - Services ▾ [Our Approach](https://www.matternenergy.com/services) [Maturity Assessment](https://www.matternenergy.com/services/maturity-assessment) [Proof of Value](https://www.matternenergy.com/services/proof-of-value) [Integration & Data Architecture](https://www.matternenergy.com/services/integration-data-architecture) [Retained Operations](https://www.matternenergy.com/services/retained-operations) - Government ▾ [Federal Capabilities](https://www.matternenergy.com/government) [Commercial Solutions Openings (CSO)](https://www.matternenergy.com/government/commercial-solutions-offerings) [OTA & Rapid Prototyping](https://www.matternenergy.com/government/rapid-prototyping) [Solutioning as a Service™](https://www.matternenergy.com/solutioning-as-a-service) [Book a Lab Session](https://www.matternenergy.com/schedule-lab-sessions) - [Insights](https://www.matternenergy.com/insights) - [Events](https://www.matternenergy.com/events) [Schedule a Call](https://www.matternenergy.com/discovery) [![Matter + Energy home](https://www.matternenergy.com/hs-fs/hubfs/matter-energy/logo/me-logo-horizontal.png?width=205&height=24&name=me-logo-horizontal.png)](https://www.matternenergy.com/) Home ▾ [Home](https://www.matternenergy.com/) [Who we are](https://www.matternenergy.com/company) [Technology Ecosystem](https://www.matternenergy.com/technology-ecosystem) [Teaming & Partnerships](https://www.matternenergy.com/teaming) Solutions ▾ [Overview](https://www.matternenergy.com/solutions) [Technology Value Management](https://www.matternenergy.com/it-financial-management) [AI Adoption & Productivity](https://www.matternenergy.com/solutions/ai-adoption-productivity) Services ▾ [Our Approach](https://www.matternenergy.com/services) [Maturity Assessment](https://www.matternenergy.com/services/maturity-assessment) [Proof of Value](https://www.matternenergy.com/services/proof-of-value) [Integration & Data Architecture](https://www.matternenergy.com/services/integration-data-architecture) [Retained Operations](https://www.matternenergy.com/services/retained-operations) Government ▾ [Federal Capabilities](https://www.matternenergy.com/government) [Commercial Solutions Openings (CSO)](https://www.matternenergy.com/government/commercial-solutions-offerings) [OTA & Rapid Prototyping](https://www.matternenergy.com/government/rapid-prototyping) [Solutioning as a Service™](https://www.matternenergy.com/solutioning-as-a-service) [Book a Lab Session](https://www.matternenergy.com/schedule-lab-sessions) [Insights](https://www.matternenergy.com/insights) [Events](https://www.matternenergy.com/events) [Schedule a Call](https://www.matternenergy.com/discovery) [Home](https://www.matternenergy.com/) / Company Who We Are # We genuinely enjoy hard problems. *Especially the ones that don't fit the template.* Matter + Energy brings together deep domain expertise, active AI research, and a broad network of TBM practitioners, software engineers, and delivery specialists — all organized around a founding conviction: the solution should fit the problem, not the other way around. Illustrative scenarios · Different problems, different right answers Problem A · Complex enterprise 14 business units, three clouds, and a legacy mainframe Requires layered allocation logic, a unified taxonomy, and phased data normalization. An oversimplified model would undermine allocation accuracy, transparency, and scalability. Problem B · Straightforward SaaS Single-tenant SaaS, one cost center, and clean billing data A simple, well-configured model delivers the visibility the business needs. Adding complexity would increase cost and maintenance without adding meaningful value. The goal isn’t the simplest solution or the most sophisticated one. It’s the right level of complexity for the problem. 15+ Years of Practitioner Experience TBM Council–Listed TBM Provider Sized to the Problem, Not the Fee Problem-First Technology Choices Automation First, AI Where It Wins Results Measured Against Agreed Baselines 15+ Years of Practitioner Experience TBM Council–Listed TBM Provider Sized to the Problem, Not the Fee Problem-First Technology Choices Automation First, AI Where It Wins Results Measured Against Agreed Baselines How We Think ## No two problems are the same. We appreciate that — *we don't fight it.* There's a version of technology consulting that works like a vending machine: describe your problem, receive the standard solution. It's efficient. It's also wrong roughly half the time — because it conflates problems that share a category label but have almost nothing else in common. An IT financial management problem at a 40,000-person federal agency with seventeen funding streams and a legacy mainframe is not the same problem as ITFM at a 2,000-person SaaS company with clean cloud billing and a single cost center. They get the same label. They require completely different approaches. We notice that difference — and we think it matters enough to build our entire methodology around it. The same is true in AI adoption. A document-processing use case for a procurement team is not the same problem as an agentic reasoning system for operational decision-making. One calls for a well-configured workflow. The other calls for rigorous evaluation, [governance](https://www.matternenergy.com/insights/governance-gap) architecture, and a much more careful conversation about what happens when it's wrong. Treating them the same isn't just inefficient — it's how organizations end up with solutions that are either dangerously over-engineered or embarrassingly underbuilt. How approach varies across problem types Well-defined · Bounded Single-entity cost model with clean data Simple configuration → fast value A well-configured ITFM platform with the standard TBM taxonomy. No custom allocation logic, no multi-layer hierarchy. In production in weeks with minimal change management. Structured · Multi-layer Enterprise with hybrid cloud and multiple business units Custom taxonomy + phased rollout Requires a cost model that reflects how the business actually operates. Allocation logic built bottom-up from real billing data. Phased by business unit to manage change. Ambiguous · High-stakes Federal agency with appropriated funding, IG oversight, legacy systems Compliance-first architecture Compliance is architectural, not cosmetic. Allocation methodology must survive IG scrutiny. Reporting structures mapped to appropriation categories, not just cost centers. Complex · Novel Multi-agency portfolio with cross-fund cost sharing and OTA structures Custom methodology + extended discovery No standard template applies. Requires a discovery session engagement to map the cost structure before any platform work begins. The discovery is the deliverable at this stage. " The best solution to a problem is the one that *solves that specific problem* — not the most sophisticated solution we know how to build, and not the simplest one we can justify billing for. We find the distinction genuinely interesting to work through. That's not a line. It's why the work doesn't get boring. Matter + Energy — how we approach every new problem Automation & Innovation ## We are excited about automation. *Not just AI-powered automation.* Innovation in automation doesn't always arrive wearing a large language model. Sometimes it's a well-designed workflow that eliminates three manual steps. Sometimes it's a trigger-based integration that connects two systems that have always been disconnected. Sometimes — and this is genuinely important to say clearly — a Python script, a scheduled job, and a well-structured API call will outperform a generative AI solution on cost, reliability, latency, and auditability. Combined. We are genuinely excited about agentic AI, about the ways autonomous systems are changing what's possible in operations and decision support, and about the governance frameworks that make those systems trustworthy. We are also committed to choosing the right tool. That commitment sometimes means recommending something less novel — and we think that's a sign of intellectual honesty, not lack of ambition. Rule-Based Automation ### Structured logic. Predictable outcomes. High reliability. Trigger-based workflows, conditional routing, scheduled processes. These approaches are fast to implement, easy to audit, and produce deterministic results. For high-volume, well-defined processes, they frequently outperform AI alternatives on every relevant metric — cost, speed, error rate, and explainability. We build them without apology. Integration & Orchestration ### Connecting systems that were never designed to talk to each other. Much of what passes for an "automation problem" is actually a data connectivity problem. The right intervention is a well-designed integration layer — APIs, event streams, transformation pipelines — that makes information available where and when it's needed. Often this unlocks more operational value than any AI overlay could. Agentic AI Systems AI ### Autonomous reasoning for problems that rules can't fully specify. When the process involves ambiguous inputs, multi-step reasoning, or decisions that can't be pre-encoded in a rule set, agentic AI becomes genuinely valuable. We design, deploy, and govern these systems through our AI Adoption practice — with our agentic automation platform for workflow orchestration and our AI governance platform to ensure they remain auditable and controllable. The number that matters 16% of AI initiatives scaled to enterprise-wide deployment *IBM Institute for Business Value, 2025 · 2,000 CEOs* ### Most AI initiatives fail *not because of the model* — but because of what surrounds it. Governance gaps, unclear success criteria, no baseline measurement before deployment, integration failures, change management that was never scoped. These are not AI problems. They are program management, data architecture, and organizational design problems that happen to involve an AI component. Our team has seen this pattern enough times to build around it — and we find the challenge of solving it well genuinely interesting. The Team ## Deep expertise across the bench — *and a wide network behind it.* Our core team brings together credentials that are genuinely rare in combination: a TBM Council founding member with deep command of the [TBM standards](https://www.matternenergy.com/it-financial-management) that define enterprise IT financial management, active AI research, structured strategic problem-solving, and hands-on delivery experience across complex enterprise and federal programs. Behind that core is a broad network — TBM practitioners, software engineers, delivery specialists — who extend our reach across programs without diluting the quality of what gets delivered. We draw on that network deliberately: the right expertise for the specific problem, not the nearest available resource. ◈ ### The TBM standard isn't something we learned secondhand. The TBM Council established the cost model taxonomy and measurement standards that now underpin enterprise IT financial management globally. One of its founding members is on our team — so our methodology starts at the standard itself, not at someone's interpretation of it. TBM Taxonomy ITFM Standards Cost Model Design ◉ ### Structured problem-solving at enterprise scale Analytical rigor, disciplined stakeholder communication, and structured decomposition of complex problems shape how we approach every engagement — from initial discovery through the conversation that closes the work. Problem Structuring Executive Communication Enterprise Strategy ◇ ### Active AI researchers who understand what the models actually do AI governance, agentic system design, and responsible deployment require an understanding of how these models actually work — their failure modes, their limitations, their susceptibility to specific kinds of misuse — not just familiarity with the APIs. Our AI practice is grounded in research, which makes our governance frameworks substantive rather than performative. Model Architecture AI Governance Responsible AI Agentic Systems ◻ ### IT and product program managers who have owned complex deployments end-to-end The gap between a technically sound solution and one that actually gets adopted is almost always a program management problem. Our delivery team brings experience running complex, multi-stakeholder technology programs — the kind where scope changes, budget conversations get hard, and organizational dynamics threaten the outcome. We've navigated those situations. We know what they look like early. IT Program Management Product Leadership Change Management Stakeholder Alignment The combination of founding-member TBM expertise, active AI research, and a broad delivery network means every engagement gets the right depth — without the overhead of an organization built to look large rather than perform well. *That's the model we've built, and it's deliberate.* [Join the Network](https://www.matternenergy.com/careers) Overview How the Solutioning as a Service™ framework works in practice. A two-page overview of the end-to-end delivery methodology — from Discovery through Evolve — and how it reduces risk across digital transformation initiatives. ↓ Download Overview Name + work email required Certifications ## The credentials behind the work. Certifications held by our team, and the frameworks we apply — from financial management to AI governance, cloud architecture and federal security. SAFe Scaled Agile Framework Agile Certified Practitioner FinOps FinOps Framework Certified ITFM IT Financial Management AI Governance AI Governance Professional AI Platform Enterprise AI Platforms AWS Cloud & Solutions Architecture CMMC Level 1 (Self-Assessment) NIST Frameworks we apply: AI RMF · CSF Registrations WOSB · EDWOSB · SDB · SWaM UEI KFTRUXU6KYA4 CAGE 9TFF7 [Federal procurement info →](https://www.matternenergy.com/government/commercial-solutions-offerings) Explore Further ## More about how we work. The pages below go deeper into the platforms we work with, the roles we're hiring for, and how to start a conversation. ### [Careers Work that measures its own impact. We work on problems that matter for organizations that can't afford to get it wrong. If you bring specific depth in TBM, software delivery, AI, or enterprise IT — and want to work on problems that are genuinely hard — we'd like to hear from you. View Open Roles](https://www.matternenergy.com/careers) ### [Contact Reach the right person directly. Whether you have a specific opportunity, a procurement question, a press inquiry, or you want to understand whether there's a fit — this is the right place to start. 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