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Production AI, engineered end to end, six eval-gated service lines.

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The same playbook, tuned to the constraints of the sectors we ship into most.

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Proof, not promises, selected case studies and recognition.

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A transparent, 3-phase playbook from first audit to embedded team.

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AI Strategy

Clarity before commitment.

Commit budget to AI with a number behind the decision, not a hunch. Our strategy sprints, architecture audits, and build-vs-buy memos quantify the opportunity, the cost, and the risk, so you and your board move forward with confidence. We can build it afterward, or hand the plan to your team.

01 · Consulting engagements

Six types of engagement.

Strategy before code. Every engagement produces a written, numbered deliverable, not slide decks and verbal recommendations.

01 · Engagement

AI Strategy Sprint

A two-week sprint that produces a written AI roadmap: prioritised use-cases, build-vs-buy recommendations, data readiness assessment, and a 90-day action plan.

02 · Engagement

Architecture Audit

A thorough review of your existing AI system (model selection, eval coverage, infrastructure reliability, and security posture) with a prioritised remediation plan.

03 · Engagement

Build-vs-Buy Analysis

Rigorous financial and technical analysis comparing custom builds against SaaS vendors and open-source options. We model the 3-year TCO, not just the sticker price.

04 · Engagement

AI Readiness Assessment

Evaluate your data infrastructure, engineering team capacity, and organisational readiness before committing to an AI build. We tell you what's missing and how to fix it.

05 · Engagement

Model Selection & Evals

Model bake-offs on your actual data and use-case. We run the evals, present the results, and make a written recommendation backed by numbers, not vendor marketing.

06 · Engagement

AI Team Upskilling

Hands-on workshops and pairing sessions to bring your engineering team up to speed on LLM engineering, RAG, and eval-first development. Knowledge transfer, not dependency.

02 · Why consultants often fail you

What we do differently.

  1. Engineers, not strategists

    Our consultants are senior AI engineers who have shipped production systems. When we tell you something is feasible, we've built it before. No inflated promises from people who've never written a line of inference code.

  2. Written deliverables, not slides

    Every consulting engagement ends with a written document: a memo, a roadmap, or an audit report. Something you can act on, share with your board, and revisit six months later.

  3. Honest about what AI can't do

    We tell clients when rules-based systems are better than AI, when their data isn't ready, and when the risk profile doesn't justify autonomy. Honesty protects both of us.

  4. No vendor kickbacks

    We recommend tools because they're the right fit, not because we have a reseller agreement. Our analysis compares vendors on your requirements, not their marketing budgets.

Proof, not promises

Twenty-plus AI systems shipped to production. One playbook, six industries, and a team that stays past launch.

AI systems live in production
20+
Senior engineers & researchers
21+
Upwork rating, 3 verified reviews
5.0
Founded in Lahore
2022
Verified Upwork clientAI product engagement · 5-star review

03 · Common questions

Before you brief us.

We don't know where to start with AI. Can you help?
Yes, this is our most common consulting entry point. We run a two-week AI Strategy Sprint that maps your business processes, identifies where AI creates the most leverage, and gives you a prioritised roadmap before any code is written.
We have an AI vendor proposal. Can you review it?
Absolutely. We do independent technical reviews of vendor proposals and SaaS AI products. We check the claims, run the evals, and give you an honest second opinion before you sign a contract.
What does a build-vs-buy analysis actually deliver?
A written memo covering: total cost of ownership over 3 years (custom vs. vendor), capability gap analysis, integration complexity, data sovereignty implications, and a final recommendation with the reasoning shown. It's the document you take into your board meeting.
How long does an architecture audit take?
Typically two weeks for a scoped system. We review your model serving, eval coverage, data pipeline, security controls, and observability, then present a prioritised finding report with severity ratings and remediation steps.

Available for new engagements

Ready to get clarity on your AI?

30 minutes, one of our seniors, no slide deck. By the end of the call you will know whether we are the right team, and if not, who is.

Or call +1 (512) 710-5701

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