Most AI pilots never ship.
I embed with your team, work on your actual systems and constraints, and take AI from demo to production — with retrieval you can audit, evals that gate releases, and a handover your own engineers can run without me.
Embedded delivery by Balkar Singh — one engineer, accountable end to end.
The demo always works.
Production is where it dies.
Getting a model to look impressive in a sandbox is the easy part. These are the four things that actually stop it reaching your users.
It sounds right and is wrong
A fluent answer with no source behind it is a liability, not a feature. Until every claim traces back to a document your organization actually owns, no one can sign off on it.
It never touches your systems
A chat window that can't write to your scheduler, your CRM, or your case management system is a toy. The work is in the plumbing, the auth, and the edge cases nobody demos.
No one can prove it still works
Without a test suite over real cases, every prompt change is a gamble. Teams stall at the pilot because they cannot answer "how do you know it didn't get worse?"
It leaves when the consultant does
A system only your vendor understands is a system you don't own. If your team can't read it, run it, and change it, you've bought a dependency.
Don't take my
word for it.
Three things that decide whether an AI system survives contact with real users. Run them yourself — every control below is live.
Ask a question against a small set of policy documents. Watch which passages get retrieved, how they're scored, and how the answer cites them. Try the third question — the answer isn't in the documents.
Retrieval
Answer
A caller books an appointment. The transcript plays on the left; on the right, watch each system get written to as the call progresses. This integration layer is where most projects stall.
Transcript
Systems of record
Before any response reaches a user it's scored against a rubric. Toggle between a good answer and a bad one to watch the harness catch the failure and block it.
Candidate response
Rubric
What I actually
build for you.
Four capability areas. Delivered against your systems, your data, and your compliance constraints — not a generic template.
Retrieval & grounding
Answers built on your own documents — policies, contracts, case files, manuals — with every claim carrying a citation back to the source passage a reviewer can open.
- Citations on every answer
- Refuses when the source isn't there
- Runs against your document store
Systems integration
The unglamorous part that decides whether any of this ships: auth, scheduling, records, telephony, and the failure paths that only show up against real infrastructure.
- Writes into your systems of record
- Handles the edge cases demos skip
- Audit trail on every action
Evals & guardrails
A test suite over real cases so a prompt change is a measurable decision, not a gamble. Responses gated on grounding, scope, and escalation before anything reaches a user.
- Regression tests on real cases
- Blocks unsafe or ungrounded output
- Escalates instead of guessing
Handover & enablement
Documentation, runbooks and working sessions so your own engineers can operate and extend the system. The goal is that you stop needing me.
- You own all code and infrastructure
- Runbooks your team can follow
- No proprietary platform dependency
AI for the ones
who need it most.
We build AI systems for nonprofits, senior homes, and public trusts across Canada — and everywhere next. Voice-activated. Accessible. No tech skills required.
Bill Payment AI
A senior says "pay my hydro bill" — the AI reads it, confirms the amount, and pays it. No computer. No login. Just a voice.
Senior Homes · NonprofitsGrocery & Delivery AI
Order groceries, schedule prescription pickups, and book meal delivery — all by speaking. No app. No account. Just ask.
Senior Care · Public TrustsAppointment AI
Books medical appointments, follow-ups, and transit rides. Sends reminders by call. Works 24/7 in any language we train it on.
Clinics · Nonprofits24/7 Community Helpline AI
An AI voice line for your nonprofit that answers questions, routes calls, and collects intake information — even when staff aren't available.
Nonprofits · Public TrustsFinancial Navigation AI
Helps clients understand bills, track spending, find government benefits they qualify for, and flag unusual charges — by conversation.
Public Trusts · Senior HomesMultilingual Access AI
AI that speaks to your community in their language. Punjabi, Mandarin, Spanish, Tagalog, Hindi — trained on real community needs.
All Mission PartnersThis isn't a product line. It's a pledge. Every business system YEINC deploys helps fund mission work for a community organization that can't afford enterprise AI. You grow — someone else gets access too.
Shipped, live,
and still running.
Every one of these is in production with a real operator depending on it. Open any of them — they are live sites, not mockups.
PB11 The Barber Club
A sharp, booking-ready site that matches the chair experience — dark, confident, built for mobile.
15+ new bookings/week onlineVisit live site →Hamsa Yoga Studio
Calm, breathable, class-schedule-ready — a studio site that feels like the practice itself.
New students booking every weekVisit live site →Boss & Friends Construction
A trades site that builds trust fast — services, proof, and a clear way to get a quote.
2 new contracts in month 1Visit live site →
GROUTES
Full identity build for Guri Baidwan's Brampton, ON venture — website, branding, and logo, delivered end to end.
Brampton, OntarioYEInc — Building Technology
Our own venture — separate from the studio. An AI technology company building intelligent agents, platforms and products for the next era. Building technology, elevating futures.
Enter the venture →Where an embedded
engineer fits.
I am not the right answer for everything. Here is the honest read on when I am — and when a consultancy or your own hire is the better call.
| Big consultancy | ★ Embedded FDE | Build the team in-house | |
|---|---|---|---|
| Time to a working pilot | × Months of discovery | ✓ ~2 weeks | × 3–6 months to hire |
| Who actually writes the code | × Juniors after the pitch | ✓ The person you met | Your team, once hired |
| Works in your systems | Eventually, via change requests | ✓ From week one | ✓ Yes |
| Evals & guardrails | Usually a later phase | ✓ Before launch, not after | Depends on seniority |
| You own the code | × Often licensed back | ✓ Fully, no lock-in | ✓ Yes |
| Cost shape | $250k+ engagements | Fixed-scope, quoted upfront | $150k+/yr per engineer |
| Long-run capability | × Leaves with the vendor | ✓ Handover is the goal | ✓ Strongest, if you can hire |
If you already have a strong platform team, hire — don't retain me. If you need it working before you can justify that headcount, start with a diagnostic →
Embedded, not
over the wall.
I work inside your constraints from day one. You see everything as it's built — there is no reveal at the end.
Discover
I sit with the people doing the work and map where the time actually goes — what systems hold the data, who signs off, what the failure costs. The output is a written diagnosis, not a proposal.
Prove
One narrow, high-value slice built against real data and real integrations. Enough to prove it works and expose what breaks — before anyone commits to scope.
Harden
Evals over real cases, guardrails, audit logging, and the failure paths. This is the phase that separates a pilot from something you can put in front of the public.
Hand over
Runbooks, documentation, and working sessions with your engineers until they can operate and extend it themselves. You keep the code and the infrastructure.
Three ways
to start.
Fixed scope, quoted in full before anything begins. No hourly billing, no change-order games. All figures CAD.
Where AI actually pays off
Two weeks embedded with your team to find the work worth automating — and the work that isn't.
- ✓ Interviews with the people doing the work
- ✓ Systems & data readiness audit
- ✓ Written diagnosis, ranked by value and risk
- ✓ A build plan you can take to anyone
- ✓ Credited back if we go on to build
One slice, in production
The highest-value slice from the diagnostic, built against your real systems and put in front of real users.
- ✓ Everything in the Diagnostic
- ✓ Retrieval grounded in your documents
- ✓ Integrated with your systems of record
- ✓ Eval suite and guardrails before launch
- ✓ Runbooks and engineer handover
Ongoing, in your team
For organizations rolling AI across several workflows who want an engineer inside the team rather than a vendor outside it.
- ✓ Everything in the Pilot build
- ✓ Multiple workflows, sequenced
- ✓ In your standups and your repos
- ✓ Upskilling your engineers as we go
- ✓ Exit plan from day one
Fixed scope, quoted upfront · You own all code and infrastructure · Start with the diagnostic →
Mission-track pricing is grant-friendly and set against your organization's capacity, not a rate card. Commercial work cross-funds it. Apply for Mission AI →
Someone who's run
the operation, not just the repo.
Balkar Singh — I've run construction crews, managed logistics operations, and studied computer programming. That combination is the whole point: I've been the person whose day gets wrecked by a broken process, and I can also go build the thing that fixes it.
Most AI work fails on the operational side, not the model side. The hard parts are the exceptions nobody documented, the sign-off nobody mentioned, and the system of record that only one person understands. I've been on the receiving end of all three, which is why I start by sitting with the people doing the work instead of with the architecture diagram.
I work as one engineer, embedded and accountable end to end. No account manager, no handoff to juniors after the pitch. And the goal is that you stop needing me — every engagement ends with your team able to run and extend what we built.
Real words,
real results.
Every system I've built is live and getting clients. Don't take my word for it.
"Balkar built our entire online presence from scratch — website, booking, the works. We went from zero to getting 15+ new client bookings online every week. Couldn't have asked for better."
"The site is beautiful. Clients compliment it every week — it feels premium, exactly like our brand. Balkar understood the vibe we wanted without us explaining it twice."
"Fast, professional and straight to the point. We needed a site that looked legit and handled job inquiries. He delivered fast — we've already picked up two new contracts from it."
The questions
that actually matter.
An engineer who works inside your organization rather than delivering to it from outside. I sit with the people doing the work, build against your real systems and constraints from week one, and stay until it runs in production. The difference from consulting is that I write the code, and the difference from a contractor is that I own the outcome, not a ticket queue.
Answers are grounded in your own documents and every claim carries a citation back to the source passage, so a reviewer can check it. When the supporting material isn't there, the correct behaviour is to say so rather than guess — and that path is tested explicitly. You can watch both behaviours in the demos above.
Every build gets an eval suite over real cases from your organization, run before anything ships. A prompt or model change becomes a measurable decision with a pass/fail result, not a gamble. Responses are also gated on grounding, scope, and escalation, so an unsafe answer is blocked rather than delivered.
It stays in your infrastructure. I build against your systems, your storage, and your access controls — no copying your documents into a platform I own. Data residency, retention and access requirements get settled in the diagnostic, before any code is written, because they shape the architecture rather than being bolted on after.
You do, completely — code, infrastructure, and documentation. No proprietary platform, no licensing it back, no dependency on me continuing. Handover is an explicit phase of every engagement, and the goal is that your engineers can operate and extend the system without me.
Then the diagnostic is exactly the right place to start. Part of its job is telling you which problems don't need AI — a lot of what gets pitched as an AI project is really a data or process problem, and paying to find that out in two weeks is much cheaper than finding it out mid-build.
Roughly two weeks to a working pilot against real data and real integrations. Getting that pilot production-ready — evals, guardrails, audit logging, failure paths — is the phase most projects underestimate, and it depends on your compliance requirements and how accessible your systems are. Both get scoped in the diagnostic so the number is honest.
Yes. Website and AI-agent work for local businesses continues and is a separate, lighter track — see the AI systems pages for that. This page is about embedded engineering work for firms and institutions integrating AI into how they operate.
Nonprofits, senior homes and public trusts get grant-friendly pricing set against their capacity rather than a rate card, cross-funded by commercial work. It is a pledge about how the practice is funded, not a separate product line. Apply through the intake and we'll work out what's realistic together.
Bring YEINC to
your community.
We support modified, localized versions of YEINC — independent chapters, regional franchises, or community-run AI programs built on our systems and adapted for your people.
Canada
British Columbia, Alberta, Ontario — senior homes, nonprofits, and businesses.
● ActiveUnited States
Community nonprofits and service businesses in major metro areas.
Coming soonUnited Kingdom
Public trust partnerships and age-care AI pilot programs.
Coming soonNigeria
Youth-led YEINC chapter serving community organizations and local businesses.
Coming soonIndia
Multilingual senior care AI and nonprofit automation across major cities.
Coming soonPhilippines
Community-driven mission AI serving barangay-level nonprofits.
Coming soonCaribbean
Regional chapter in development — public trust and senior care focus.
Coming soonFind out where you
actually stand.
Six questions, about a minute. You get a readiness read and a recommended first step on screen — before I ask for anything. If AI isn't the right answer for your situation, it will say that too.