Marlabs becomes a frontier AI firm with Copilot 365, GitHub Copilot and Dynamics 365
How does an AI-first mandate change daily work? The customer story, "Marlabs becomes a frontier AI firm with Copilot 365, GitHub Copilot and Dynamics 365," shows how Marlabs uses Microsoft 365 Copilot, GitHub Copilot, and Copilot Studio to improve employee workflows and build AI solutions for clients. Read the story to learn from Marlabs' experience.
How is Marlabs becoming an AI‑first company?
Marlabs is reimagining itself as an AI‑first company by embedding Microsoft’s AI tools across its own business before taking those learnings to clients.
Internally, Marlabs has adopted
Microsoft 365 Copilot,
GitHub Copilot, and
Copilot Studio to reshape how employees work, how software is engineered, and how projects are delivered:
- Business functions: Microsoft 365 Copilot supports everyday work like document summarization, email drafting, research, and proposal development. After a series of adoption workshops, Marlabs reports a 56% productivity gain across the organization.
- AI agents for operations: Using Copilot Studio, Marlabs has built a set of internal agents (for HR, onboarding, approvals, contracts, proposals, and financial/operational data). These agents automate routine tasks and free teams to focus on higher‑value work.
- Engineering practices: GitHub Copilot is now “foundational” to the engineering lifecycle. Developers work about 20% faster, and the quality improvements are enabling new solution offerings for clients.
These internal wins have shaped
AgilityAI, Marlabs’ enterprise AI transformation suite. It packages proven, reusable “agentic accelerators” so clients can adopt similar AI patterns—especially in regulated industries like financial services and life sciences, where Marlabs emphasizes security, compliance, and Microsoft’s built‑in protections.
By using AI across its own business first, Marlabs can guide clients with practical, hands‑on experience rather than theory.
What concrete results has Marlabs seen from Copilot and AI agents?
Marlabs has already seen several measurable outcomes from its AI initiatives:
- HR virtual agent: A Copilot Studio–based HR agent unifies multiple HR systems into a single conversational experience. Employees can apply for leave, check policies, and resolve questions in seconds. This has:
- Reduced HR response times by more than 60%
- Eliminated the previous help desk system
- Shifted about 80% of HR queries to the Copilot agent
- Onboarding agent: An onboarding agent streamlines new‑hire processes and saves roughly three days per new employee, accelerating time‑to‑productivity.
- Engineering productivity: GitHub Copilot has become central to the software development lifecycle. Marlabs reports that developers now work about 20% faster, with a noticeable uplift in code quality. This has also evolved into a client service, helping customers adopt GitHub Copilot for similar gains.
- Organization‑wide productivity: With Microsoft 365 Copilot supporting everyday tasks (summaries, emails, research, proposals), Marlabs has seen a 56% productivity gain across the company.
- Client value and pricing: Because of these efficiencies, Marlabs now includes a 20% cost savings in proposals for work that uses AI, encouraging clients to reinvest those savings into further strategic AI initiatives.
These results are not just internal efficiency wins; they also serve as reference patterns Marlabs uses when designing AI solutions and business cases for its clients.
How does Dynamics 365 and Copilot fit into Marlabs’ long‑term AI vision?
Marlabs is modernizing its delivery engine with
Microsoft Dynamics 365 Project Operations, strengthened by Copilot, to create a more unified, AI‑powered system of record for projects.
Today, this means:
- Centralizing project timelines, resources, financials, and performance data into a single, AI‑enabled platform.
- Connecting Dynamics 365 Project Operations with Marlabs’ growing ecosystem of Copilot Studio agents.
- Using this integrated data to power AI‑driven forecasting, risk detection, and workflow automation across the full project lifecycle.
Looking ahead, Marlabs’ vision is “one AI as the UI”:
- A universal conversational interface where specialized agents work together behind the scenes.
- Employees and clients interact with a single interface that can surface data and insights from across systems—HR, engineering, finance, delivery, and sales.
- Plans to migrate the existing external‑facing website agent to Copilot so it can answer questions about Marlabs’ services, adopt a sales persona, and even provide customized solution teasers for prospective clients.
In this model, tools like GitHub Copilot “transform how software is built,” Dynamics 365 Project Operations “transforms how projects are run,” and Copilot Studio agents orchestrate workflows—together reshaping how Marlabs and its clients operate in an AI‑first world.

Marlabs becomes a frontier AI firm with Copilot 365, GitHub Copilot and Dynamics 365
published by Mayhem Shield
More about us
Mayhem Shield is an independent, buyer-side assurance practice for enterprise AI deployments. When an organization is preparing to approve an AI tool for production, a coding assistant, a RAG pipeline, an agentic system, its approval forums need evidence of how the implementation will actually operate in that environment, not a vendor marketing pack. That evidence is what we produce.
We do not sell, implement, or operate the AI products we review. We are paid only by the buyer, never by the vendor. That separation is the product: it is what makes our findings defensible in front of security, architecture, risk, and audit stakeholders.
How we work
- Structured, repeatable review logic. Phases, evidence rules, severity calibration, and gate criteria are defined in advance, not invented per engagement. The methodology is published and inspectable on GitHub without a sales call.
- Grounded in your environment. Findings are tested against your identities, data paths, integrations, and workflows as actually deployed, not against the vendor's reference architecture.
- Decision-ready outputs. Every engagement ends in a written position: go, conditional go, or no-go, with a traceable findings register, evidence requests, and conditions tied to POC, pilot, and production gates.
Core capabilities
- AI implementation assurance reviews. Fixed-structure packages from a two-week rapid readiness review of one tool through a portfolio program covering three or more tools under one assurance standard.
- Architecture and trust-boundary analysis. Deployment model, data flow, identity, and integration scope for AI systems, documented in formats governance forums already recognize.
- AI vendor claim verification. Assessment of whether a vendor's published security and data-handling claims are checkable, contractual-only, or unverifiable, before those claims underwrite an approval.
- Security and governance advisory. Buyer-side support for AI review boards, evidence standards, and approval gate design.
We maintain relationships with major cloud and technology providers for market and technical visibility. Because our work is buyer-side assurance, we take no resale margin or implementation fees from any vendor, and any relationship relevant to a specific review is disclosed to the client at scoping.
Our commitment
Approvers carry personal and organizational risk when they sign off on an AI deployment. Our job is to make sure they sign with evidence in hand. For more information, visit www.mayhemshield.com or contact us at info@mayhemshield.com.