Value driven engagement from the first workshop to production systems

Technology programs often stall in the gap between a strategy discussion and the first production release, when the people who shaped the vision hand it to a team that has to rebuild the context. Simform runs one connected journey through workshops, discovery, accelerator-led proofs of concept, and delivery, so each early decision is tested against what can be built, governed, and scaled in your environment.

Workshops

Programs lose months when business leaders, architects, and delivery teams carry different ideas of what AI or modernization should achieve. Simform’s hands-on workshops bring those groups together with working tools, from envisioning sessions that rank priority use cases to build-along formats such as Microsoft’s Agent in a Day, where your teams create a working agent in Copilot Studio within a single session.

What you leave with

Shortlist of use cases ranked by value and feasibility
Shared language across business and engineering stakeholders
Hands-on experience with the target platform
Clear decision on what moves into discovery

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Discovery

A use case that looks simple on a whiteboard can depend on incomplete data, systems that resist integration, or controls your security team has yet to approve. Simform’s discovery sprints examine architecture, data readiness, workflows, and compliance needs with your stakeholders, then convert those findings into developer-ready requirements, a target architecture, and a sequenced roadmap with effort and cost attached.

What you leave with

Current-state assessment of systems and data
Target architecture and integration plan
Prioritized backlog of developer-ready user stories
Delivery roadmap with team shape, milestones, and estimates

Start with Discovery

Proof of Value and Demo

Approval often hinges on seeing the idea work with your own data, and a prototype built from scratch can outlast the patience of the people funding it. Simform starts proofs of concept from its AI accelerators, including ThoughtMesh for knowledge agents, TrueMorph for data warehouse modernization, and NeuVantage for legacy code analysis, so the effort goes into your use case. For Microsoft-led programs, our Frontier Enterprise Envisioning Demo shows Fabric, Azure AI Foundry, Copilot Studio, and Power Platform working together as one enterprise blueprint before a first workflow is funded.

What you leave with

Working demo in your data environment
Success criteria agreed before the build begins
Measured results against those criteria
Recommendations with a production plan

Explore our Accelerators

Outcome Delivery

Momentum from a successful POC fades quickly when production work starts with a team that has to relearn the context. Simform carries discovery artifacts and POC findings directly into co-engineering pods that work inside your tools and rituals, with ALM and DevOps metrics, daily reporting, and executive reviews keeping progress visible. Delivery runs on the agentic SDLC practices Simform has proven within its own engineering teams.

What you leave with

Production releases on an agreed cadence
Foundation, Innovation, and New Initiative pods sized to your roadmap
KPI dashboards and regular executive reviews
Full IP ownership with complete engineering documentation

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Scale and Run

Launch is where real usage begins to test the assumptions made during design. Simform’s application, cloud, and AIOps managed services keep systems reliable and cost-accountable after go-live, while product sustenance and the next round of workshops keep the roadmap moving toward the following use case.

What you leave with

Ongoing application, cloud, and AIOps operations
Reliability and cost reporting your finance and engineering leads both use
Continuous improvement backlog
Direct route back into workshops for the next initiative

Explore Managed Services

What you get

Six commitments that hold across every stage of the journey.

Outcome accountability

Dedicated technical lead manages the engineering team end to end and takes priorities directly from you, so accountability carries through from advisory work into delivery.

Reusable accelerators

Prebuilt architecture, workflows, and integrations from Simform’s AI accelerators remove repetitive setup, so early budget goes into the parts of the solution specific to your business.

Engineering specialists

Architects, data scientists, AI engineers, and UX designers join the engagement when a decision needs their depth, without you hiring for skills needed only for a few weeks.

Progress driven by KPIs

Milestones, velocity, quality, and blockers are tracked through ALM and DevOps KPIs and reviewed in weekly demos and executive check-ins.

Complete IP ownership

You own all IP for paid-for work, protected by NDAs and strict contracts, with documentation and handover support that let your teams run and extend what was built.

Co-engineering model

Simform’s Core-Flexi resourcing model keeps a stable core team while specialist pods ramp up or down as priorities shift.

Let's talk

Hiren Dhaduk

Creating a tech product roadmap and building scalable apps for your organization.

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From Data to Action: Unlocking Agentic AI for Mission - Critical Work

Value driven engagement from the first workshop to production systems

Workshops

What you leave with

Shortlist of use cases ranked by value and feasibility

Shared language across business and engineering stakeholders

Hands-on experience with the target platform

Clear decision on what moves into discovery

Discovery

What you leave with

Current-state assessment of systems and data

Target architecture and integration plan

Prioritized backlog of developer-ready user stories

Delivery roadmap with team shape, milestones, and estimates

Proof of Value and Demo

What you leave with

Working demo in your data environment

Success criteria agreed before the build begins

Measured results against those criteria

Recommendations with a production plan

Outcome Delivery

What you leave with

Production releases on an agreed cadence

Foundation, Innovation, and New Initiative pods sized to your roadmap

KPI dashboards and regular executive reviews

Full IP ownership with complete engineering documentation

Scale and Run

What you leave with

Ongoing application, cloud, and AIOps operations

Reliability and cost reporting your finance and engineering leads both use

Continuous improvement backlog

Direct route back into workshops for the next initiative

What you get

Outcome accountability

Reusable accelerators

Engineering specialists

Progress driven by KPIs

Complete IP ownership

Co-engineering model

Let's talk