You can work with NeoTek Solutions in Nashville in six ways, from a short AI readiness assessment to a dedicated delivery team or skilled professionals on your own team. Most engagements start with a free consultation. We learn your goals, recommend the smallest useful first step and confirm scope, team and commercial model in a written proposal.

This page explains each engagement model, our four-stage process, who does what and how we keep you informed. To see how we protect quality at every step, read our quality approach.


Engagement Models

AI Readiness Assessment

We run a structured review of your data, systems, skills and processes to find where AI can help. It fits leaders who know AI matters but are unsure where to start. You get a prioritized list of use cases, the gaps to close first and a practical roadmap.

It usually ends with a decision on one or two use cases worth proving. Many clients continue with a proof of concept or ongoing AI strategy consulting.

Proof of Concept

We build a small, time-boxed proof of concept (PoC) that tests whether an AI idea works on your real data. It fits teams with a promising use case and open questions about accuracy, cost or fit. You get a working prototype, evaluation results against agreed success criteria and an honest recommendation.

A PoC ends with a clear go, adjust or stop decision. When the answer is go, it moves into project delivery.

Project Delivery

Project delivery means we own an agreed outcome, such as an AI assistant, an automated workflow or a custom application. It fits organizations that want a defined result without growing their own team first. You get working software, documentation, runbooks and knowledge transfer.

Our engineers use AI-assisted methods under senior review, described on our AI-accelerated development page. Projects end with handover to your team or continue with ongoing support.

Dedicated Delivery Team

We assemble a stable, cross-functional team that works through your backlog over time. The team draws on our Nashville and Hyderabad offices. You keep a single Nashville-based point of contact for priorities, escalations and planning.

It fits organizations with a steady stream of AI, data or software work. You get consistent people who learn your systems, plus predictable planning. The engagement continues while the backlog justifies it, and the team can scale up or down with notice.

IT Staff Augmentation

We add screened AI, data, cloud or software professionals to your team, working under your direction. It fits managers who already run delivery but need specific skills or extra capacity. You get vetted candidates, interview support and interim or continuing placements.

Placements end when your need ends, or they continue as long-term support. Learn more about our AI and IT staffing services.

AI Advisory

We provide ongoing senior guidance without standing up a full delivery team. It fits leaders who want an independent second opinion on vendors, architecture, governance or roadmap choices. You get regular working sessions, reviews of your plans and vendor proposals, and written recommendations.

Advisory usually runs as a monthly retainer and can be paused or ended when your team is self-sufficient.


Our Engagement Process

The diagram shows four stages, Discover, Prove, Build and Run, with a decision point between each and a loop from Run back to Discover.

NeoTek Solutions engagement processFour stages in a left-to-right flow, Discover, Prove, Build and Run, with a decision point between each stage and a feedback loop from Run back to Discover for the next use case. A Prove result can return for adjustment, and governance through status updates, sprint demos and steering reviews runs across every stage.AdjustNext use caseSTAGE 1DiscoverGoals, dataand use casesSTAGE 2ProveWorking prototypeon real dataSTAGE 3BuildIterations withworking demosSTAGE 4RunMonitor, support,improveUse case agreed?Scope and success criteriaGo, adjust or stop?Based on evaluation resultsReady to release?UAT and client sign-offGovernance: status updates · sprint demos · steering reviewsDecision pointReturn or feedback loop

Discover

We interview stakeholders, review your systems and data, and map the workflows involved. Together we define the business problem, success measures and constraints such as security and compliance.

Deliverables include a use-case shortlist, a data and systems summary, risks and a recommended next step. The decision point is agreement on one scoped use case and its success criteria.

Prove

We build a thin, working version on real or representative data. We test it against the success criteria agreed in Discover and share results openly, including what did not work.

Deliverables include the prototype, evaluation results, an architecture outline and a delivery plan. The decision point is a go, adjust or stop call based on evidence.

Build

We deliver in short iterations with a working demo at the end of each one. Every change passes code review, automated tests and security scans, and AI features pass evaluation before release.

Deliverables include production-ready software, documentation, runbooks and trained users. The decision point is release readiness, confirmed by user acceptance testing and your sign-off.

Run

We deploy, monitor and support the system in production. For AI features, we watch accuracy, cost and drift, which is the gradual decline in quality as data changes.

Deliverables include monitoring, support, improvement recommendations and knowledge transfer. The decision point is whether to hand over, keep improving or start Discover on the next use case.


Your First Weeks With Us

Here is what to expect once the proposal is signed:

  1. Kickoff

    We meet your sponsor and key stakeholders to confirm goals, scope, success measures and ways of working.

  2. Access and onboarding

    Your IT team grants least-privilege access to the systems and data we need, following your policies.

  3. Shared workspace

    We set up the shared backlog, the status report format and the meeting schedule.

  4. Early discovery

    Our team interviews users, reviews data and confirms assumptions made during the proposal.

  5. First plan review

    We walk you through the detailed plan, risks and first iteration goals before building starts.

  6. First demo

    You see early working output and tell us what to change.

Where it helps, our Nashville team can meet you onsite for kickoff and key workshops.


Team Roles

  • Engagement leadYour main point of contact, accountable for scope, schedule, risks and communication.
  • Solution architectDesigns the architecture, data flows, security approach and integration with your systems.
  • Engineers and data scientistsBuild the software, data pipelines, models and AI features, using AI tools under senior review.
  • QA engineerPlans and runs testing, maintains automated tests and checks AI output quality.
  • Your executive sponsorSets priorities, removes blockers and makes the go or stop decisions.
  • Your product ownerOwns the backlog, answers business questions and accepts completed work.
  • Your subject-matter experts and IT teamProvide domain knowledge, access, security review and future ownership.

Communication and Governance

  • Regular status updatesA short written report covers progress, next steps, risks, decisions needed and budget position.
  • Sprint demosAt the end of each iteration you see working software, not slides.
  • Steering reviewsSponsors from both sides review outcomes, risks and priorities at agreed intervals.
  • Shared backlogYou can see every task, its status and its priority at any time.
  • Risk managementWe keep a risk log with owners and mitigations, and raise new risks early.
  • Change managementScope changes are written up with their impact on cost and schedule. Nothing changes until you approve it.

Commercial Models

We do not publish prices, because cost depends on scope, team and timeline. Your proposal confirms the model and the estimate. We commonly use three models:

  • Fixed scopeA set price for a clearly defined deliverable. It suits readiness assessments, proofs of concept and well-specified projects.
  • Time and materialsYou pay for the effort used. It suits evolving requirements, dedicated teams and staff augmentation.
  • Monthly retainerA regular fee for agreed ongoing capacity. It suits AI advisory and post-launch support.

How Can NeoTek Solutions Help You Choose the Right Engagement?

You do not have to know the model you need before you call. Telling us the outcome you want is enough for us to propose one.

  • Work we deliverReadiness assessments, proofs of concept, full project delivery, dedicated teams, staff augmentation and ongoing advisory, in whatever combination your plans need.
  • Sized to your teamWe start with the smallest useful step, then scale the team up or down with notice as your backlog, budget and priorities change.
  • Clear before you commitScope, team and commercial model go into a written proposal first, and every later scope change is priced before you approve it.
  • How we workShort cycles with AI-assisted delivery and human review, success criteria agreed early, and a working demo at the end of each iteration.
  • Skills on the teamAI and machine learning engineers, data engineers, cloud and security specialists and QA in one team, under a single engagement lead who owns your schedule.
  • What makes us differentWe are vendor-neutral rather than reselling one platform, and our Nashville headquarters meets you onsite while our Hyderabad office adds delivery capacity.

Tell us what you want to achieve and by when, and we will recommend the model that fits when you book a free AI consultation.


Frequently Asked Questions

How do I start working with NeoTek Solutions?

Book a free consultation through the contact page. We learn your goals, recommend the smallest useful first step and send a written proposal with scope, team and commercial model before any work starts.

Which engagement model will NeoTek Solutions recommend for us?

We recommend a readiness assessment when you are unsure where AI fits, and a proof of concept when you want a specific idea tested. For build work we propose project delivery or a dedicated team, and staff augmentation when you run delivery yourself.

Can we start small with NeoTek Solutions before committing to a large project?

Yes, and we prefer it. We start most clients with an assessment or a proof of concept. We put a decision point at the end of every stage, so you commit to the next one only when the evidence supports it.

How does NeoTek Solutions use its Nashville and Hyderabad offices?

Dedicated delivery teams can draw on people from both offices. Every client keeps a Nashville-based point of contact. Working hours and meeting times are agreed at kickoff.

Who owns the code and deliverables?

You do. Clients own the code, documentation and intellectual property created for their project. Your code and data are not used to train public AI models.

How are changes to scope handled?

Every scope change is written up with its effect on cost and schedule. Work on the change begins only after you approve it, and the shared backlog is updated.


Take the First Step

Tell us what you want to achieve, and we will recommend the right way to start. You can also begin on your own with our free AI readiness assessment. Book a free AI consultation