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Selected work

Real client work, not lab demos.

LimeShift shows business context, delivery scope, and operating change from real work across multiple company types.

Use this page to judge range, operating depth, and the quality of the delivery thinking.

Book assessment call About LimeShift
Client confidentiality Business outcomes and scope, handled with professional discretion
Range across the business Leadership, commercial, operational, and compact-team examples
Disciplined claims Conservative proof language instead of inflated case-study promises

How the work is shared

  • Real clients and real business context
  • Clear before-and-after operating change
  • Claims kept conservative
  • Readable for leadership review

Buyer evidence

For teams comparing AI consulting and automation partners across Bulgaria and the EU.

This is the evidence route: public client context, case-study links, delivery scope, and the guardrails LimeShift uses when AI work touches real operating workflows.

Consultant fit

Judge how LimeShift thinks before a sales call.

The work is framed around workflow ownership, decision support, review points, and adoption rather than vague transformation language.

Local and EU context

Bulgaria-based delivery with EU operating expectations.

The public pages describe how privacy, governance, and practical rollout shape automation work for leadership and B2B teams.

Proof boundary

Public proof without confidential overreach.

Use the case studies to understand context and operating change; do not infer private systems, data, vendors, or economics.

Featured case studies

Case studies that show range without oversharing.

Each case study gives enough context to understand the business situation, the scope of work, and the change that followed.

How to evaluate the work

Judge range, operating depth, and discipline.

The important question is whether the work changed live execution in a way leadership could use and trust.

  • Judge business range

    Look for work that reaches several functions and both multi-team and compact businesses, not only one narrow automation story.

  • Judge operating depth

    The useful signal is whether the work changed how execution runs, how leadership sees it, and how teams actually use it week to week.

  • Judge credibility

    Strong case material should feel specific enough to trust and conservative enough to believe.

Proof discipline

Claims stay conservative because credibility matters.

LimeShift states what can be supported clearly: client context, workflow scope, operating change, and the type of outcome created.

  • Real client context

    Case material starts from real company situations, real operating pressure, and work that moved beyond demos.

  • Conservative claims

    The case material avoids vanity dashboards, exaggerated ROI promises, and benchmark theatre.

  • Professional discretion

    Client confidentiality is treated as part of delivery quality, not as a marketing inconvenience.

  • Clear operating change

    Case studies show the before state, what changed, and why that change mattered to the way the business works.

For boards and leadership teams

Use the governance page if you need the oversight view as well.

It covers the questions leadership should be able to answer once AI starts touching business-critical workflows.

Open the governance page

Go deeper

Read the case studies and articles together.

The case studies show where the work landed. The blog explains the operating choices behind rollout, governance, proof discipline, AI SEO, and founder-led execution.

Services Assessment Department route Company route Case studies Proof checklist Blog

Next step

Use the assessment call to decide where this should turn into action.

If the range and delivery style fit what your business needs, the next move is a focused conversation about the highest-leverage workflow, team, or leadership layer to start with.

Book assessment call See department route