At 365mesh, we often refer to AI outcomes as AI Products rather than universal “solutions”. Why?
Because our work doesn’t end at proof-of-concept as it culminates in living, integrated, and maintained software products that deliver ongoing value.
Products imply ownership, lifecycle, user adoption, performance, and evolution. These products may be internally oriented (used by your teams) or externally oriented (delivered to customers or partners), but in both cases, they are designed to deliver repeatable, measurable outcomes while continuously driving business value creation.
Solutions solve a problem once; products sustain and adapt to changing needs over time.
Explore our AI-Powered Organisations — where intelligence is purpose-built to generate measurable business outcomes. This is your starting point to understand how 365mesh delivers AI as a core strategic enabler, not just a technical add-on.
At 365mesh, we specialise in designing, building, and scaling AI-powered software that solves real problems. Our solutions are:
- Customer-Centric: aligned to the workflows, decisions, and goals of your teams
- Scalable: ready for operational deployment across your organisation
- Flexible: available as embedded SaaS intelligence or fully tailored deployments
Whether you are augmenting human decision-making or automating complex processes, we partner with you to:
- Clarify the role AI will play in your organisation
- Define a path from pilot to production
- Deliver business-aligned value quickly
Our team brings years of experience and deep expertise in AI use case discovery, architecture, data strategy, and product design ensuring your AI initiatives are aligned with business strategy and deliver measurable business impact.
Let’s build AI products that create impact from day one and scale confidently over time that are designed for your organisation and you industry.
AI-Driven Opportunities
AI opens the door to a new class of business opportunities some that optimise what already works, and others that unlock entirely new value streams. At 365mesh, we help organisations identify where AI can generate competitive advantage, operational efficiency, or differentiated experiences.
We work with our clients to frame these opportunities through four lenses:
- Augmentation: Enhancing human capabilities, speeding up insight, or improving decision quality leading to greater productivity and accelerating the quality or speed of value creation in your organisation.
- Growth Enablement: Using AI to scale your core offerings faster, personalise customer experiences, unlock new revenue channels, and sustain expansion across markets or segments.
- Automation: Streamlining processes, reducing manual effort, and eliminating repetitive work — reducing costs, minimising error impact, and freeing up resources for strategic priorities.
- New Capability: Creating entirely new services, business models, or market positions that would not be possible without AI helping your organisation enter new markets or reshape your competitive edge.
These lenses help identify transformation potential across key business domains:
- Process & Operations: Improve agility, responsiveness, and resource efficiency
- Business Models: Explore AI-driven monetisation, productization, and platform plays
- Value Chain: Optimise or reconfigure what to own, partner, or outsource
- Organisational Culture: Shift mindsets toward experimentation, intelligence, and trust in automation
- Time-to-Market: Reduce the cycle time between insight, build, and deploy
- Customer Experience: Deliver smarter, more relevant, and adaptive experiences at scale
Example opportunities include:
- Building AI-native digital products
- Enabling real-time responsiveness with predictive insights
- Transforming customer experience via intelligent interfaces
- Increasing asset uptime and utilisation through AI-driven monitoring
- Designing autonomous decisioning pipelines for operations or logistics
We prioritise opportunities that align to business goals, demonstrate early value, and scale over time. Every engagement starts with identifying the opportunity landscape and choosing the most valuable place to begin.
AI+ vs +AI
AI+
AI is the core of the product, creating value. These are AI-native solutions where intelligence defines the product’s purpose and market differentiation. AI is not added – it is the product. Think intelligent interfaces, autonomous reasoning systems, or real-time recommendation engines.
Use AI+ when:
- The product exists because AI is the main driver of value
- The intelligence layer is integral to the customer experience
- The model or system is continuously improving or adapting to generate value
AI+ requires dedicated data infrastructure, close collaboration across business, product, data, and engineering teams, and a strong feedback loop for iterative improvement.
+AI
AI is in the product, enriching capabilities. These are products where AI enhances features, increases automation, or provides smarter insights, however the core utility remains possible without AI.
Use +AI when:
- The product already exists and AI is used to improve outcomes or usability
- The intelligence layer is modular or additive
- AI serves as a behind-the-scenes enabler (e.g., predictive routing, anomaly detection, smart tagging)
+AI is often easier to implement incrementally, with faster time-to-value and lower technical risk, especially in mature platforms with low levels of technical debt.
This distinction helps stakeholders align expectations across strategy, resourcing, and delivery:
- AI+ aligns with product innovation and category creation
- +AI aligns with operational improvement and user experience uplift
We help organisations select the right pattern or hybrid model based on their goals, technical maturity, and market positioning.
Consumption models
AI is not a one-size-fits-all proposition, and neither is its delivery. Our consumption models are designed to reflect where you are in your digital maturity, how much internal capability you want to build, and how quickly you want to realise value.
We offer three flexible pathways:
Build-to-Operate (AI-as-a-Product)
- Custom-designed solutions fully owned by the client
- Deployed in your private or public cloud tenancy
- Includes agile delivery, agile managed services, continuous performance monitoring, and site reliability engineering
- Ideal for long-term ownership, business agility, compliance needs, and flexible integration
- 365mesh, as AI Software company, works with a range of trusted AI Infrastructure partners and vendors, including Cloud Providers and NVIDIA OEM partners
- Your data, intellectual property and code remain yours and serves as a key differentiator driving insight relevance, and competitive edge
SaaS AI (AI-as-a-Feature)
- Ready-to-use AI embedded directly into 365mesh products
- Delivered as a service via secure, scalable cloud infrastructure
- Low-friction onboarding with continuous updates and improvements
- Ideal for fast outcomes with minimal internal overhead
- 365mesh delivers SaaS products guided by transparent product roadmaps – with input from customers who help shape future features
- Your data remains yours and serves as a key differentiator driving insight relevance, and competitive edge
Many of our flagship products including IoT, Video Analytics, Asset Intelligence, and Digital Twin have cutting-edge AI-powered features that are natively integrated, continually improved, and immediately actionable.
Co-Developed, Experimental & Edge AI
- Collaborative development of AI modules and edge-enabled solutions tailored to your systems, platforms, or devices
- Designed to modernise existing digital products or embed AI into net-new applications
- Ideal for partners with product roadmaps, platform strategies, or OEM ambitions
- Includes co-design of AI models, joint sprint planning, and shared engineering for full transparency and IP clarity
- 365mesh manufactures AI-enabled sensors with onboard processing and integrates them with NVIDIA Jetson-class edge hardware for real-time local inference
- IP ownership models are defined upfront and shaped by contribution, licensing, or commercial agreements
- Code delivery can be structured as source, containers, libraries, or embedded components depending on your integration model
- Best suited for organisations seeking embedded intelligence at the edge, robotics solutions or differentiation in software-hardware offerings
Each model is supported by robust lifecycle services:
- Governance, monitoring, and explain ability
- Scalable data and model pipelines
- Continuous improvement options
We’ll help you choose the right model or blend to maximise both time-to-impact and sustainability.
Operational Models
Developing and maintaining non-SaaS AI product successfully requires more than choosing the right technology it depends on having the right operational model to support adoption, governance, and value creation. At 365mesh, we offer adaptable operating models that reflect how AI fits into your business and delivery teams.
We help clients design their AI operating model across five dimensions:
Ownership Model
Centralised
A single AI team governs and delivers all AI initiatives across the organisation on behalf of executive sponsors.
Federated
AI capabilities are embedded within business units, with each executive sponsor directly driving AI-centric value for their domain.
Hybrid
A central AI platform supports embedded AI champions who represent the priorities of their respective executive sponsors.
Delivery Model
Internalised
Your teams design, build, and operate the full AI lifecycle.
Partner-led
365mesh leads design, delivery, and operation delivered either as SaaS features or a dedicated ‘build-to-operate’ AI product.
Co-delivered
Joint teams collaborate on delivery, with aligned roadmaps, shared execution, and defined ownership boundaries.
Integration Depth
Surface-level
AI as standalone tools or dashboards; loosely connected to operational systems.
Embedded
AI tightly integrated into business systems, user interfaces, or workflow logic.
Autonomous
Agentic AI operates independently, making or executing decisions with minimal human input.
Lifecycle GRC
Structured oversight across AI application, data, and model deployment, monitoring, drift detection, and retraining workflows.
Clear role accountability for managing data quality, model performance, fairness, bias, explain ability, and compliance over time.
Audit-ready versioning and traceability of both datasets and models.
Alignment with internal policies (e.g. privacy, security, ethical AI), AI risk frameworks (e.g. NIST AI RMF), and evolving regulatory standards (e.g. EU AI Act, ISO 42001).
Optional automation for documentation, approvals, and compliance reporting at scale.
Change Enablement
Training and adoption programs tailored to AI literacy levels across technical, operational, and leadership roles
Business process mapping and operating rhythm adjustments to support AI-driven workflows and decision cycles
Metrics aligned with value realisation and continuous improvement — including impact tracking at model, process, and business levels
Our goal is to help you run AI like a product — with clearly defined ownership, operational structure, lifecycle governance, and continuous feedback loops. We co-design AI operating models that embed delivery and accountability across your teams, integrate seamlessly with your delivery methodologies, and ensure that AI becomes a durable capability within your organisation. The result: AI product that is technically robust, operationally scalable, and aligned to your strategic and regulatory environment.
AI Journey
There’s no single path to becoming an AI-powered organisation — but successful journeys tend to follow a set of high-value phases. At 365mesh, we guide clients through an AI journey that’s iterative, measurable, and deeply aligned to organisational goals.
Opportunity Framing
Opportunity Framing to answer why to clarify the business motivation and strategic rationale for applying AI before investing in experimentation, data acquisition or model selection.
- Identify business problems where AI has the potential to unlock measurable value
- Distinguish between AI+ (AI as the product) and +AI (AI within the product) approaches to shape scope and expectations
- Prioritise use cases based on business impact, technical feasibility, data readiness, and urgency
- Define clear success criteria aligned to business outcomes, not just model performance
- Engage a committed business sponsor to champion the initiative, secure cross-functional alignment, and own the value case
Experimentation & Validation
Identify How
- Develop low-risk prototypes or proofs-of-value to test hypotheses
- Validate technical feasibility, integration complexity, and projected business impact using real or synthetic data
- Engage stakeholders early to co-design desirable user experiences and identify adoption risks
- Assess data availability, operational fit, and potential bottlenecks before scaling further
- Refine solution scope and success criteria ahead of productization
Productization
This is where 70% of enterprise AI initiatives fail – not due to technical limitations, but because of breakdowns in ownership, integration, and culture.
- Transition from prototype or proof-of-value to a fully production-grade AI product
- Establish scalable model pipelines, APIs, monitoring, and governance processes
- Embed AI into live workflows, digital platforms, and digital infrastructure
- Drive process modernisation by aligning legacy operations with new data-driven decision cycles
- Invest in cultural enablement including stakeholder buy-in, role clarity, and incentives to adopt and trust AI in daily workflows
- Ensure cross-functional collaboration across business, data, engineering, ops, and product teams to sustain delivery momentum
Operationalisation
Make It Work
- Define ownership, metrics, and lifecycle responsibilities across product, data, and engineering teams
- Deploy within your chosen operating model and consumption model, ensuring fit with business constraints and scale expectations
- Establish run-time processes for model monitoring, drift handling, retraining, and performance reporting
- Integrate into enterprise delivery practices such as MLOps, DevOps, and GitOps to support continuous improvement
- Clarify support, change management, and release rhythms across environments
Scale & Sustain
Extend the Value
- Expand successful AI products across business units, geographies, or adjacent use cases
- Enable continuous retraining, performance tuning, and data feedback loops to keep outcomes relevant
- Strengthen enterprise-wide literacy and platform reuse through playbooks, accelerators, and community of practice
- Embed AI into your broader transformation roadmap not as a one-off project, but as a new way of working
- Periodically reassess ROI, strategic alignment, and ecosystem impact to guide next-phase investments
This journey is intentionally non-linear. Some organisations begin with experimentation, others with integration or operational uplift. Our role is to meet you where you are – whether clarifying the why, testing the how, scaling what works, or embedding AI as a product. We accelerate your progress with the right combination of products, partnerships, and operating models designed to turn AI from promise into durable capability.
Business Outcomes of AI-Powered Products
Faster Time-to-Value
- Reduce the time from idea to insight to impact
- Launch AI features or products in weeks, not quarters
- Reuse accelerators, playbooks, and modular components for rapid deployment
Improved Decision Accuracy
- Use AI to enhance or automate high-impact decisions
- Reduce reliance on intuition with real-time, explainable recommendations
- Improve confidence in decisions across operations, finance, and strategy
Productivity at Scale
- Augment teams with AI to reduce manual effort and improve output quality
- Accelerate core processes like planning, forecasting, and quality assurance
- Free up resources to focus on strategic tasks, not repetitive work
New Revenue Channels
- Monetise AI-driven features within existing platforms
- Launch entirely new AI-powered products, tools, or services
- Unlock platform opportunities through embedded or edge AI capabilities
Cost Optimisation
- Streamline operations and reduce waste through intelligent automation
- Optimise spend across infrastructure, labour, and data processing
- Drive savings through predictive maintenance, demand forecasting, or fraud detection
Faster Innovation Cycles
- Use AI experimentation frameworks to test and learn rapidly
- Shorten product iteration loops with continuous feedback from data and users
- Enable agile AI practices like MLOps and model-driven development
Operational Resilience
- Reduce risk of error, bias, or oversight through governed AI systems
- Build robust data and model pipelines for sustained performance
- Establish accountability frameworks for explainability, compliance, and ethics
Data Advantage
- Transform raw data into reusable strategic assets
- Achieve real-time data-to-decision capability with embedded pipelines
- Maintain control of your data and IP, even in co-developed AI partnerships
Strategic Differentiation
- Position AI as a core product capability, not just a bolt-on
- Build competitive edge through proprietary models, data, and edge capabilities
- Align AI initiatives with executive priorities and transformation roadmaps
Cultural Shift Toward Data-Driven Operations
- Raise AI literacy and confidence across business functions
- Foster cross-functional collaboration between product, data, and ops
- Embed continuous improvement into your AI lifecycle
Common Pitfalls & Mistakes
We’ve seen what makes AI succeed and what holds it back. Here are the most common pitfalls that stall progress or lead to limited results:
No clear business sponsor
AI projects without a committed executive owner often lose focus or fail to connect with strategic goals.
Treating AI as a one-off project
Success requires product thinking with ownership, lifecycle management, and continuous improvement.
Lack of operational readiness
Great models won’t survive without scalable pipelines, clear governance, and integration into daily workflows.
Overinvesting in tech, underinvesting in adoption
Without process changes, training, and cultural enablement, even the best models won’t deliver sustained value.
Chasing perfection instead of momentum
Waiting for “perfect” data or models often delays impact. Iteration with real feedback is key.
Data without readiness or clarity
Poor data quality, unclear ownership, or lack of access can stall even the most promising use cases.
Neglecting governance, risk, and compliance (GRC)
Skipping early planning for explainability, accountability, and regulatory compliance invites future blockers.
No plan to scale
AI that works in a lab or pilot setting may fall short when extended across teams, geographies, or business units.
At 365mesh, we help organisations avoid these traps by aligning strategy, design, engineering, and operations from day one — so AI becomes a sustainable capability, not just a technical exercise.
industries
AI+ Industries
- Digital Platforms & SaaS
- Robotics, Drones & Autonomous Systems
- Smart Cities & Digital Infrastructure
- Environmental Monitoring & Biodiversity
- Smart Devices & Edge Products
- OEMs & Edge AI Manufacturers
- AI-Driven Digital Twins
- Cyber-Physical Systems & IoT
- AI Product-Led Ventures
- Developer Tools & AI APIs
Industries (+AI): AI enhances existing systems
+AI Industries
- Mining & Large Infrastructure
- Utilities & Water Management
- Transport & Mobility
- Construction & Asset Inspection
- Healthcare & Aged Care
- Retail & Distribution
- Facilities Management & Real Estate
- Education & Workplace Enablement
- Public Sector & Government
- Insurance & Risk Services
- Financial Services & Asset Management
- Agriculture & Smart Farming
- Logistics & Supply Chain
- Telematics & Smart Vehicles
Delivering value to organisations building AI-driven products as well as those embedding AI to enhance existing services, operations, or decision-making.
Use Cases
Vertical & Cross Industry
365mesh supports a range of AI use cases that fall into two broad categories: vertical use cases, which are highly specific to an industry, and cross-industry use cases, which apply widely across sectors.
Vertical use cases are tightly coupled with domain-specific processes and context, for example, AI-powered leak detection for water utilities or visual defect detection on a mining site. These use cases often require specialised data, integration with legacy systems, and alignment with sector-specific regulations. They benefit from deep industry knowledge and tailored operational models.
Cross-industry use cases, on the other hand, are reusable solution patterns that can be applied across multiple domains. Examples include forecasting, anomaly detection, natural language interfaces, and document intelligence. These use cases are ideal for organisations looking to adopt proven AI patterns with broad applicability and faster time-to-value.
365mesh delivers value for organisations building AI-driven products as well as those embedding AI to enhance existing services, operations, or decision-making.
| Use Cases | Business Outcome | Consumption Model | Operational Model |
| Clinical Trial Monitoring (Healthcare) | Accelerate insights, ensure protocol adherence | Built-to-operate AI Product (Cloud or AI POD) | Hybrid, with embedded clinical users |
| Claim Triage & Fraud Detection (Insurance) | Speed up resolution, reduce leakage | SaaS AI or Embedded Module | Centralised analytics, federated ownership |
| Credit Risk Scoring (Finance) | Improve loan decisioning, reduce bad debt | Built-to-operate AI Product (Cloud or AI POD) | Internalised with regulatory oversight |
| Autonomous Equipment Analytics (Mining) | Improve safety, reduce downtime and optimise load cycles | Built-to-operate AI + Edge AI | Site-specific, partner-delivered |
| Supply Chain Optimisation | Reduce lead times, increase reliability and throughput | Built-to-operate AI Product (Cloud or AI POD) | Federated deployment with feedback loops |
| Portfolio Sentiment & Risk AI (Finance) | Monitor signals and optimise exposure | Built-to-operate AI Product (Cloud or AI POD) | Internalised or co-delivered with product |
| Precision Agriculture Analytics | Improve yield, reduce resource input | 365mesh IoT + Edge AI | Field-embedded with agritech integration |
| Digital Twin for R&D Infrastructure | Optimise lab/facility utilisation, track experimental variance | 365mesh Digital Twin (SaaS or Embedded) | Internalised by research teams |
| Maintenance Automation (Industrial) | Reduce downtime and labour costs | Built-to-operate AI Product (Cloud or Edge) | Co-delivered or embedded with OEM workflows |
| Asset Condition Monitoring | Reduce unplanned downtime and extend asset lifecycle | 365mesh Asset Management (SaaS AI) | Centralised ownership, partner-led |
| Worksite Safety & Compliance | Detect risks in real time, improve incident response | 365mesh GreenMesh (SaaS AI with edge integration) | Federated ownership, embedded AI champions |
| Video Intelligence & Perimeter Security | Automate detection of threats, reduce manual surveillance load | 365mesh BroadSecure (SaaS AI for video analytics) | Centralised or hybrid, with site-specific rules |
| Predictive Maintenance & Diagnostics | Lower servicing costs, increase equipment uptime | IoT + Industry Decks (SaaS AI) | Internalised or co-delivered with templates |
| Digital Twin for Fleet & Facilities | Simulate and optimise performance of real-world systems | 365mesh Digital Twin (SaaS AI) | Centralised, scalable via GitOps + telemetry |
| Forecasting & Demand Planning | Improve accuracy in resource allocation | AI-as-a-Feature (within 365mesh platforms) | Partner-led, model-based feedback loops |
| Smart Energy & Environmental Tracking | Reduce energy usage, improve sustainability reporting | 365mesh GreenMesh (SaaS AI) | Federated delivery across multiple locations |
| Hazard Detection (Edge CV) | Prevent incidents through real-time detection | 365mesh GreenMesh + Edge AI | Embedded with on-site ops and analytics teams |
| Compliance Automation (Forms & Docs) | Reduce manual review cycles and error rates | AI Module (SaaS or API) | Internalised governance, federated delivery |
| Personalised Customer Engagement | Increase retention and lifetime value | SaaS AI + CRM Integration | Hybrid or internalised |
AI POV to Product
Turning a proof-of-value (POV) into a production-grade AI product is where most organisations struggle — not due to technical capability, but due to the lack of ownership, integration strategy, and delivery rhythm.
At 365mesh, we help clients move from isolated experiments to embedded AI capability. This includes:
- Clarifying product ownership, accountability, and long-term value measures
- Designing scalable pipelines, APIs, and feedback loops for continuous improvement
- Aligning architecture, infrastructure, and integration points across platforms or devices
- Modernising processes and stakeholder behaviours to support sustained delivery
- Choosing the right operational and consumption model for your product’s context
Regardless of whether you are scaling a proven POC or starting from scratch, we’re here to help turn your AI ideas into real, lasting business results.
AI Accelerator
The 365mesh AI Accelerator is built for business decision makers who need to move fast with clarity, confidence, and real outcomes.
In 6-12 weeks, we help your team validate high-impact use cases, build working AI components, and lay the foundations for scale. Designed to be vendor-neutral but partner-enabled, the Accelerator gives you flexibility – with access to leading AI tools, platforms, and infrastructure without locking you into any single vendor.
What’s included:
- Joint delivery sprints tied to measurable business outcomes
- Reusable architecture and AI components aligned with your environment
- Deployment-ready solutions across cloud, edge, or hybrid platforms
- Executive-level reporting on value, risk, and scale readiness
- Flexible handover or co-delivery, based on your internal capability
We bring the partners, frameworks, and proven patterns – you bring the challenge. Together, we turn it into momentum.
AI Partners
365mesh works across the AI value chain with a curated ecosystem of partners — from infrastructure to software, delivery to regulation. This model allows us to stay vendor-neutral while giving clients access to world-class capabilities.
We collaborate with
Channel Partners
We work with distribution and value-added resellers (VARs) who enable broader market access, bundled offerings, and streamlined procurement especially in regulated or enterprise environments.
AI Software Vendors
We integrate best-in-class platforms, frameworks, and model lifecycle tools into our products and client solutions selecting based on fit, not lock-in.
We are an AI Software Delivery Company (ISV)
365mesh delivers its own suite of AI-powered SaaS products and builds tailored AI solutions for clients using our proven frameworks and delivery models.
We support both AI+ (AI is the product) and +AI (AI in the product) use cases, and offer build-to-operate and consumption-ready options.
AI Infrastructure Vendors
We design and deploy solutions using hardware and infrastructure from leading OEMs and cloud providers supporting cloud, on-premises, and edge environments.
AI Infrastructure Delivery Partners
Where advanced deployment or enterprise integration is required, we team up with trusted infrastructure specialists to deliver secure, scalable foundations for AI.
Resellers
We support selected resellers and solution providers with white-label-ready or co-branded of SaaS AI products, enablement programs, and technical integration kits helping them unlock new revenue streams in AI.
Regulators & Standards Bodies
We align our delivery, governance, and operational models with globally recognised standards to ensure transparency, trust, and compliance across markets.
This includes:
- NIST AI Risk Management Framework (USA)
- ISO/IEC 42001 – AI Management Systems
- EU AI Act (Europe)
- OECD AI Principles
- Responsible AI Guidelines (e.g. Singapore IMDA, Canada AIO)
- Local privacy, data protection, and cybersecurity legislation (e.g. Australian Privacy Act, GDPR, PDPA, CCPA, HIPAA)
How We Deliver AI
So, you’ve explored the use cases, figured out how AI fits your operating model, and you’re ready to start. But why 365mesh?
Since 2020, we’ve been building and deploying AI products that actually get used, not just tested. Our experience spans SaaS platforms, AI-powered applications, cloud-native systems, custom edge deployments, and production-grade AI PODs.
You might be modernising an existing platform, launching something new, or scaling a proven idea – we bring the tools, models, and delivery approach to move fast and make it real.
Here’s how we deliver:
Modular, Composable Building Blocks
We bring a library of proven components from cloud pipelines and MLOps to edge inference and embedded analytics that slot into your stack and accelerate delivery.
AI-as-a-Product, Not a Project
Every initiative is treated like a product with defined owners, measurable outcomes, embedded feedback loops, and a roadmap for iteration and scaling.
Embedded Partnership
Our teams work shoulder-to-shoulder with yours across technical, business, operations, and product — to ensure what we deliver fits your environment and delivers meaningful impact.
Vendor-Neutral, Partner-Enabled
We integrate with best-in-class technologies including NVIDIA, Microsoft, AWS, GCP, Dell, Cisco and open-source while staying independent and flexible to your needs.
Built for Production
We design solutions with production in mind including monitoring, governance, retraining workflows, and lifecycle management so your AI capabilities are sustainable, not stuck in pilot.
From edge deployments and AI PODs to SaaS and cloud-native delivery, 365mesh delivers AI that is built to run, scale, and deliver results.
Turn readiness into results with AI
Build & Launch With Us
When you’re ready to get moving, we meet you where you are – and move fast.
We help organisations go from idea to production through structured design sprints, co-creation workshops, and lean delivery practices. Whether you’re extending your own platform, standing up a net-new AI product, or embedding AI in physical environments, we help shape, build, and launch it.
Bring us an idea, a pain point, or even a prototype. We’ll help turn it into something real with:
- Fast-start engagements that align use case, data, and business model
- Flexible delivery: SaaS, cloud-native, edge, or build-to-operate models
- Access to AI accelerators, tools, and technical partnerships
- Clear scope, shared ownership, and tangible outcomes
We don’t just build proof-of-concepts. We build products that deliver with the right mix of technology, governance, and operational clarity to scale.
If your organisation is strategically aligned to deliver real AI-driven business outcomes beyond experimentation – we want to hear from you.