Services

From product uncertainty to documented software work you can build

ITNeuroNet helps founders and business owners turn early ideas, risky requirements, scattered data, and AI experiments into software work with clear scope, documentation, and a plan you can build from.

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You do not need a perfect specification to begin. You need enough clarity to make the next technical decision without creating avoidable risk.

Each service is built around a decision a founder or team needs to make: what to build first, how to structure the system, how to use AI without losing control, whether the data is ready, or where technical risk is hiding.

Decision aid

Choose the problem you need help with.

Filter services by your current situation. Not sure? Leave it on All and start with an assessment.

8 of8 services shown

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MVP

Validate Your Product Idea

Product & Technical Discovery

When to use it

You have an idea or a workflow concept, but it is still unclear who the users are, what the first release should include, what data is needed, and which integrations matter.

What you get

01A summary of the product context, including users, workflows, and constraints
02An MVP boundary recommendation, including what should wait
03A map of risks and assumptions across the product, data, and integrations
04An initial architecture direction and the recommended next step

What decision it supports

Whether the idea is ready to become a project, what the first slice should be, and which risks you should answer before spending heavily.

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MVPArchitecture

Plan Your MVP

MVP Sprint

When to use it

You are past validation and need a defensible v1 plan before you hire developers, brief a vendor, or commit budget.

What you get

01MVP scope with included, excluded, and deferred capabilities
02Primary user journeys and critical edge cases
03Functional requirements and an initial data model
04Delivery milestones and a readiness checklist for implementation

What decision it supports

What belongs in v1, what is intentionally left out, which assumptions remain, and how the first build should be sequenced.

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Architecture

Turn Requirements Into Delivery

Architecture & Delivery Sprint

When to use it

You already have requirements, but key details are still not written down: how the system is split, who owns which data, how integrations should connect, where task boundaries are, and when work should be reviewed.

What you get

01An architecture document with system boundaries and rationale
02A data model, API contracts, and integration responsibilities
03A task breakdown suitable for human or AI-assisted implementation
04A quality strategy, delivery plan, and log of unresolved decisions

What decision it supports

Decide which system boundaries, interface contracts, data entities, and delivery order will make the work possible to build and easy to review.

Proof

TodaiHealth

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AIMVP

Build Your AI-Assisted MVP

AI-Assisted Product Development

When to use it

You want to move faster, but you still need clear requirements, a sound system design, tests, code review, and software that someone can maintain later.

What you get

01Working product increments tied to documented scope
02Implementation tasks mapped to the requirements and architecture notes
03Test-aware delivery with reviewable acceptance criteria
04Code review, architecture review, and handoff artifacts

What decision it supports

How to use AI in delivery without ending up with generated code that nobody has properly reviewed

Proof

TodaiHealth, AIspeaky

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Automate Workflows With AI Agents

AI Agents & Workflow Automation

When to use it

You need AI support inside a real operational process, and a generic chatbot demo would break as soon as it has to handle tools, exceptions, permissions, or live data.

What you get

01Agent workflow design with jobs, states, inputs, and handoffs
02Tool access, permissions, and human review model
03Data access plan and integration architecture
04Prototype or production-ready implementation plan

What decision it supports

What the agent is allowed to do, which tools and data it can use, where people need to review its work, and how failures are handled.

Proof

Echo Speech Analytics

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Data

Make Your Data AI-Ready

Data Engineering & Analytics

When to use it

Reporting, automation, or AI work is blocked by scattered sources, inconsistent metrics, undocumented data, or fragile exports.

What you get

01Data source inventory with owners and quality concerns
02Pipeline and orchestration design
03Data model, data mart, or semantic layer
04Reporting foundation and AI-ready access patterns

What decision it supports

Which pipelines, models, metric definitions, and access patterns need to be in place before dashboards or agents can be trusted.

Proof

Echo Speech Analytics

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Audit

Audit or Guide Your Technical Direction

Technical Audit & Fractional CTO

When to use it

Something in the vendor work, codebase, roadmap, architecture, or delivery process does not look right, and you want an independent senior opinion.

What you get

01Technical audit memo with findings and business impact
02Review of architecture, data, security, and delivery risks
03Prioritized recommendations by urgency
04Guidance on roadmap, vendors, hiring, or advisory support

What decision it supports

Whether to continue, restructure, rebuild, change vendors, hire differently, or stabilize the current technical direction.

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Compliance

Build Safely Around Healthcare and Sensitive Data

Healthcare & Compliance-Aware Systems

When to use it

PHI, PII, regulated workflows, vendor-controlled data, or other sensitive operational information are part of the project from the start.

What you get

01Sensitive data flow notes for PHI, PII, vendors, and transfer points
02System boundary model for internal and external actors
03Access control and auditability plan
04Secure AI provider routing and compliance-aware documentation

What decision it supports

Which data boundaries, access rules, audit trails, and provider routing rules need to be defined before the system is built

Proof

TodaiHealth, AIspeaky

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Every project starts with a short assessment to define scope, identify risks, check timeline assumptions, and choose the right way to work together.

Discovery, sprint, retainer, and fractional support are available, depending on the stage of your project. Public price ranges are not listed because each engagement is scoped to the actual context.

Next step

Not sure which service fits your situation?

Send a short assessment request. I will review your situation and suggest whether you need discovery, MVP planning, architecture, implementation, data work, an audit, or compliance-aware system design.

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