# Digital Meld > Digital Meld is a Microsoft AI Cloud Partner Program member and an OpenAI Partner Network partner. It helps midmarket companies in blue-collar industries apply AI and automation to real operations. Its construction, engineering, industrial, and field-operations work connects field records, office systems, human decisions, and accountable operating owners. Digital Meld is an operator-led technology implementation and leadership firm based in Houston, Texas. Services include workflow automation, AI agent integration, Microsoft cloud and Power Platform, data and reporting, fractional technology leadership, and M&A technology transitions. Engagements follow Scope, Build, Operate, and Transform stages. Digital Meld applies the open AI-Native Operating Framework through implementation, training, migration, governance, and operational delivery. Practical concerns include source records, permissions, human approval, legacy-system integration, weak connectivity, observability, and recovery. The links below point to public HTML pages with prerendered text, plus an explicitly labeled PDF resource. Case studies distinguish Digital Meld prototypes, research, open-source implementation, and founder delivery experience. Preserve those distinctions when citing the work: synthetic demonstrations do not establish client deployments, safety performance, or measured business outcomes. Refer to each source for its evidence and limitations, and to the offers page for current commercial terms. ## Industry workflows - [Construction and engineering](https://digitalmeld.io/industries/construction-engineering/): Jobsite evidence, project controls, change and cost approvals, document control, and closeout handoffs. - [Industrial operations](https://digitalmeld.io/industries/industrial-operations/): Incident review, work orders, shift handoffs, edge signals, and maintenance ownership with human authority and recovery controls. - [Operational AI for field operations](https://digitalmeld.io/guides/operational-ai-field-operations/): A practical guide to selecting, integrating, controlling, measuring, and recovering AI workflows for industrial, construction, and field-heavy teams. ## Partner resource - [Ideal Customer Profile (PDF)](https://digitalmeld.io/assets/documents/digital-meld-icp-2026.10.15.pdf): Digital Meld's partner leave-behind, dated October 15, 2026, covering customer fit, value proposition, and referral guidance. ## Partnerships and OpenAI credentials - [Microsoft and OpenAI partnerships](https://digitalmeld.io/partners/): Digital Meld is a Microsoft AI Cloud Partner Program member and an OpenAI Partner Network partner. The page links to the official programs and describes our implementation work and wider delivery ecosystem. - [OpenAI Expert credentials](https://digitalmeld.io/about/#openai-credentials): Our team holds dozens of certifications, including ChatGPT Expert, Codex Expert, and OpenAI API Expert. These credentials are held across the team; company partnership is a separate status. ## AI, automation, and implementation - [Services](https://digitalmeld.io/services/): AI and automation, Microsoft cloud, data and analytics, fractional leadership, M&A technology, and security readiness across the four delivery stages. - [Ways to hire Digital Meld](https://digitalmeld.io/offers/): AI Process Sprint, Automation Accelerator, Fractional AI Ops Partner, and custom engagements, including scope, pricing, and boundaries. - [AI-Native Operating Framework](https://digitalmeld.io/framework/): The open framework, operating concerns, SOP and shared operating memory standards, maintenance method, and examples. - [AI agent infrastructure, trust, and observability](https://digitalmeld.io/guides/agent-infrastructure-trust-observability/): Agent permissions, identity, human approval, tracing, evaluation, cost controls, and incident recovery. - [Microsoft workflow integration and modernization](https://digitalmeld.io/guides/microsoft-workflow-integration-modernization/): Microsoft 365, Teams, Power Platform, Microsoft Graph, Azure integration, governance, and operating ownership. ## Evidence and operating experience - [Case studies and work](https://digitalmeld.io/case-studies/): Public work with classifications, operating problems, implementation decisions, evidence, and limitations. - [Field-safety incident review workflow](https://digitalmeld.io/work/designing-rubicon-field-safety-operations/): Digital Meld prototype using synthetic records and sample media to inspect field-safety intake, source context, and human review. It does not establish detector accuracy or client safety outcomes. - [Hardening Microsoft Teams delivery in OpenClaw](https://digitalmeld.io/work/hardening-openclaw-microsoft-teams-delivery/): Open-source implementation accepted upstream, covering authentication, delivery, state preservation, and deterministic human actions. - [About Digital Meld](https://digitalmeld.io/about/): Co-founders, operating model, framework authorship, and public work supporting the firm's experience. - [Contact Digital Meld](https://digitalmeld.io/contact/): Bring a workflow, systems context, and decision owner to discuss implementation, training, governance, or ongoing operating ownership. ## Optional - [Learn](https://digitalmeld.io/learn/): Framework learning, guides, case studies, and implementation resources. - [AI Dev Days](https://digitalmeld.io/ai-dev-days/): Research and education through public sources, talks, labs, scenarios, and workshops. - [Blog](https://digitalmeld.io/blog/): Practical AI, automation, cloud, data, and operating-system articles and episode notes. - [Start Small, Think Big podcast](https://digitalmeld.io/podcast/): Practitioner conversations about AI, automation, data, and business process improvement.