Legacy engineering workflows
Important projects rely on disconnected, aging applications and repetitive manual work that slows delivery, and every new integration means connectors built by hand.
We are building intelligent systems that connect engineering software, accelerate infrastructure research, and help cities plan and prioritize better public spaces.
Critical decisions depend on software, standards, and spatial data that rarely work together as one system.
Important projects rely on disconnected, aging applications and repetitive manual work that slows delivery, and every new integration means connectors built by hand.
Codes, research, and climate-risk evidence can be difficult to compare and verify, and codes are slow to update as climate change and resilience needs reshape the dimensions of infrastructure.
Teams in the global south need scalable ways to assess streets, benchmark them against well-designed streets in the global north, and plan phased improvements with costs.
Three complementary product areas designed around the realities of engineering work: reliable tools, traceable evidence, and accountable decisions.
Use AI to generate the connectors and MCP servers that link existing CAD, GIS, structural analysis, surveying, road-design, and quantity-estimation software with AI agents and validated engineering tools.
Develop research workflows to compare engineering standards and technical literature, and to draft new codal provisions, standards and guidelines for municipalities, rural municipalities and federal governments as climate change and infrastructure resilience change the dimensions of the challenge.
Develop geospatial workflows that compare street views of places in the global south with well-designed streets in the global north, then develop phased improvement plans and cost breakdowns for global south nations.
DIWLAM's differentiation is the intended workflow: connect existing tools and evidence, use purpose-built analysis rather than unsupported guesses, and make every consequential output easier for a professional to inspect.
Rather than asking teams to replace their established CAD, GIS, road-design, surveying, structural-analysis or quantity workflows, AI would generate the connectors and MCP servers that expose each tool to agents, which would coordinate defined tasks across them.
The planned research workflow would help specialists locate relevant clauses, compare editions and standards, and examine how research or hazard evidence relates to a design question. It would then draft new codal provisions, standards and guidelines for municipalities, rural municipalities and federal governments as climate change and resilience needs change infrastructure dimensions, as proposals for the competent authority to review and adopt, never as authoritative code.
The intended workflow would combine authorized imagery, GIS layers and municipal and rural municipal asset information to compare street views of places in the global south with well-designed streets in the global north, then develop phased plans and cost breakdowns for global south nations—not automatically issue construction-ready designs.
The intended platform connects information and tools while keeping qualified professionals in control of consequential decisions.
Use AI-generated connectors and MCPs to bring together engineering software, technical documents, geographic datasets, and existing project information.
Apply AI-assisted research, geospatial analysis, and validated calculation tools to relevant context.
Prepare preliminary designs, technical reviews, draft standards and guidelines, phased plans, cost estimates, and traceable reports.
Enable qualified professionals to verify assumptions and results and approve consequential decisions.
DIWLAM's vision is to apply AI where it can fit into established work, draw on technical evidence, and support decisions about the built environment.
AI-generated connectors and MCP servers may let agentic workflows automate established processes while organizations keep the tools and data systems they depend on.
Infrastructure planning needs transparent ways to examine changing hazards, design assumptions, and the evidence behind technical guidance, and ways to draft updated codes, standards and guidelines as conditions change.
Geospatial intelligence can help public teams in the global south benchmark their streets against the best of the global north and phase limited resources over time.
These are the architectural objectives DIWLAM intends to validate as the platform develops.
Work with existing software through AI-generated connectors and MCPs.
Use validated tools and documented calculations.
Retain sources, assumptions, versions, and review history.
Keep professionals accountable for engineering decisions.
Build complementary products on a shared foundation.
A staged approach intended to test reliability and usefulness before expanding scope. No delivery dates are implied.
Build focused prototypes, test defined engineering workflows, and validate data handling and calculation reliability.
Planned directionWork with engineering, municipal and rural municipal partners to evaluate accuracy, usability, and potential time savings.
Partner-dependentConnect the product areas through shared knowledge, geospatial context, tools, and auditable workflows.
Long-term ambitionTrust has to be designed into the workflow—not added as a claim after the fact.
Use documented assumptions and appropriate engineering calculation routines.
Keep source references and relevant standards versions visible for review.
Design for reviewable records of inputs, outputs, and changes.
Plan for access controls and responsible handling of connected data.
Require qualified professional oversight for safety-critical decisions.
Respect software licenses, data rights, and imagery usage restrictions.
Public bodies, development institutions, and programs shaping infrastructure in the region. Shown for sector context; no endorsement or partnership is implied.
No. DIWLAM is early-stage. The capabilities on this page describe what we are building and validating, and no delivery dates are implied.
No. The platform is designed so qualified professionals review assumptions and approve consequential decisions. It supports engineering judgement; it does not substitute for it.
That is not the intent. The aim is to connect the CAD, GIS and analysis tools teams already use, wherever that is practical.
We are speaking with investors, engineering organizations, municipalities, rural municipalities and technical partners. Use the form below to start a conversation or to explore a focused pilot.
DIWLAM is exploring conversations with investors, engineering organizations, municipalities, rural municipalities, and technical partners to validate and develop this vision.