AI engineering consultancy
Senior engineers, in-house AI agents. Ship in weeks, not quarters.
ESARC pairs principal engineers with a fleet of in-house AI agents so a small team can outship a large one without the Big-4 drag.
Estimate AI ROI
Put one AI workflow into business-case math before you book a call.
Model the annual value of reclaimed time, avoided rework, opportunity cost, delivery complexity, and the engagement shape that fits. No ESARC rates or public pricing.
What kind of AI surface?
Pick the closest workflow. Defaults shift by category, then you can tune the numbers.
Annual business case
$285,300
This is the estimated value of reclaimed time and avoidable rework. It is not ESARC pricing.
Recommended first step
Build Sprint- Hours reclaimed
- 1,794 hrs
- Opportunity cost
- $269,100
- Rework savings
- $16,200
- Implementation complexity
- Medium-high
- Confidence
- 74%
How the math works
- Manual load
- 20 hrs/week x 3 people x 50 weeks
- 3,000 hrs/year
- Effective coverage
- 65% target coverage adjusted for sensitive risk
- 60%
- Time value
- 1,794 reclaimed hrs x $150/hr
- $269,100
- Rework reduction
- 8% current rework x 45% reduction assumption
- $16,200
Why this engagement shape
The business case is concrete enough to pick one production surface and ship it behind an eval gate.
Related ESARC work
Shipped for, and with
Built on
How we’re different
Three things make this engagement model possible.
01
Senior-only
No junior offshore pyramid. Principal engineers in your repo, your Slack, your standups, leading the build, not handing it off.
9+ years shipping. Meta, Amazon, McGraw Hill on the resume.
02
AI-native delivery
Our in-house agent fleet writes, reviews, and tests code alongside our principals. The result is senior throughput without turning the engagement into a staffing pyramid.
Agents draft, test, review, and keep the principal focused on hard calls.
03
Production-grade
Evals, observability, security, rollback. We ship systems that survive contact with real traffic, not demos that fall over on Monday.
Sidney Voice AI runs live calls. RAG over real EHR data.
Three ways we engage
Pick the shape that matches your problem.
Recent work
All case studies →What our principals shipped last quarter.
How we work
Three phases. No surprises.
Scope
A principal sits with you for a week. Reads the codebase, talks to the people. You get a written plan, not a slide deck.
Sprint
Principal plus agents in your repo. Daily PRs. You see what landed, what broke, what comes next. No black box.
Handoff
Runbook, evals, on-call rotation if you want it. Your team owns it on day one. We stay on call for 30 days.
Partners
Senior operators behind the work, not a staffing pyramid behind a pitch.
Founder & Partner, Principal Engineer
Vaibhav Malhotra
Vancouver, BC
Principal engineer with production AI work across Meta, Amazon, McGraw Hill, Scrubs Co-Pilot, Stuf Storage, Springhouse, and MyMethod.
Partner, AI Engineering
Bhimesh Chauhan
AI systems and engineering leadership
Engineering leader for AI-powered products, clinical documentation, RAG systems, biomedical data infrastructure, IoT platforms, and enterprise ML integrations.
Tell us what you’re trying to ship.
A principal engineer reads every inbound. We reply same day on weekdays, with an honest read of whether we’re the right team for the work.