ai_consulting --help

AI Systems Consulting

Strategic guidance for startups and SMBs exploring AI.

7+ years building production AI decisioning systems

Available nights & weekends only
400K+ messages/day on production systems
99.9% uptime across multi-channel pipelines
200+ teams served by internal engineering platforms

services --list

01

AI Readiness Assessment

$100/hr

Comprehensive evaluation of your current state and AI opportunities. I'll analyze your data, workflows, and technical infrastructure to identify where AI creates the highest leverage.

Written assessment report Opportunity mapping ROI projections Implementation roadmap
02

Architecture Review

$500

Deep-dive review of your existing or planned AI architecture. I examine your technical design, data pipelines, model serving infrastructure, and scalability considerations.

Architecture document review Code/system review Detailed recommendations doc 60-min discussion call
03

Strategic Advisory

Let's talk

Ongoing advisory for AI strategy, team structure, vendor selection, and technical decision-making. Think of me as your fractional AI engineering lead for critical decisions.

Ad-hoc guidance Technical decision support Vendor evaluation Team hiring advice

process --workflow

Intro Call

Free 30-minute call to understand your challenge and determine if we're a good fit.

$ calendly book --duration 30min

Scope

I dive deep into your systems, data, and requirements. Depending on scope, this takes 1–3 days.

$ ./assessment.sh --thorough

Engagement

You receive written recommendations, architecture suggestions, or strategic guidance tailored to your specific situation.

$ cat deliverables/report.md

Delivery

Optional follow-up call to discuss findings and answer questions about implementation.

$ schedule follow-up --optional

whoami --consulting

Production Experience

7+ years shipping AI decisioning systems at Capital One scale. I've seen what works and what breaks at millions of users.

Hands-On Engineer

Still writing Python and reviewing PRs daily. I understand the real constraints of building vs. just advising from the sidelines.

Focused Scope

I work nights and weekends only. This keeps my advice sharp and ensures I'm not stretched thin across too many clients.

Decisioning Systems

Specialized expertise in AI-driven decisioning platforms, event-driven architectures, and real-time inference systems.

// technologies

Python AWS Lambda Apache Kafka TensorFlow/PyTorch Microservices Serverless Event-driven ML Pipelines

contact --booking

Book a Call

Schedule a free 30-minute intro call via Calendly. We'll discuss your needs and see if there's a fit.

$ calendly book --intro

Email Inquiry

Prefer email? Send me a message describing your project, timeline, and what you're looking for.

$ mail -s "AI Consulting" aman.tewary@live.com

Availability Notice

I currently consult nights and weekends only (after 6 PM EST weekdays, flexible weekends). This ensures I can give your project focused attention while maintaining my full-time role at Capital One.

Typical response time: 24–48 hours

faq --list

Do you build the systems, or just advise?

I focus on advisory and architecture, not implementation. I help you design the right approach, review your plans, and guide your team — but I won't be writing production code for your project.

What types of companies do you work with?

Primarily startups and SMBs that are exploring AI but don't have dedicated ML expertise in-house. I help you avoid common pitfalls and design systems that can grow with you.

How is pricing structured?

Assessment is hourly ($100/hr). Architecture Review is a flat $500. Strategic Advisory is custom — let's discuss scope and I'll propose a rate.

What's your timezone and availability?

I'm based in Toronto (EST) and available weeknights after 6 PM and weekends. I use Calendly to make scheduling easy across time zones.

Can you sign an NDA?

Absolutely. I'm happy to sign a standard NDA before we discuss sensitive details. Just mention it in our intro call.

kickoff --next-step

Share your current architecture, timeline, and AI goals. You will get a practical recommendation path in the first call.

$ book_intro_call