A small team
of agent specialists,
obsessed with shipping.
We started 2MDA in 2019 because we kept watching SMEs pay enterprise prices for AI projects that never reached production. Today we're a focused agency in Toronto, building agentic systems for companies of 30–500 people.
AI as a tool,
not a luxury.
The default story for AI is enterprise transformation — a Big-4 deck, a $2M rollout, a working pilot 18 months later. That model can't reach the small and mid-sized businesses that make up 90% of the economy.
We exist to flip it. Our engagements are sized for SME P&Ls — fixed-fee, 6–10 weeks to first production agent, a 90-day outcome guarantee. We bring senior engineers into your business, ship something real, and hand it over. No "transformation team," no consultant farm.
If you're a 50-person services firm drowning in inbox triage, or a 200-person manufacturer with three weeks of monthly close, an agent can absorb a meaningful slice of that work. We'd like to show you which slice.
From data analytics
to agentic systems.
We began as a four-person data analytics consultancy. By 2022 it became clear that the highest-leverage thing we could build for clients wasn't a dashboard — it was the system that acted on the dashboard.
So we re-tooled around agentic AI. Today we operate in three lanes: strategy (where to deploy), build (the agent itself), and operate (running it in production until your team takes over).
Every team member has shipped at least one production agent. We hire engineers who like accounting, supply chain, and procurement — not just LLM benchmarks.
Five values, in order.
Production beats prototype.
Demos are easy. We measure ourselves on agents that survive contact with real users, real edge cases, and Monday morning.
Read-only first.
Every agent starts with read-only access and human-in-the-loop. We earn write access through evals, not promises.
"This won't work" is a valid answer.
Half our intro calls end with us telling you not to build the thing. The other half become our best clients.
The boring 80%.
LLMs are 20% of an agent. Logging, evals, retries, escalations, observability — that's where the real engineering lives.
You own it, eventually.
Every engagement ends with your team in the driver's seat. We're not building a moat — we're building something you can run.
Quantified or it didn't happen.
Every project starts with a baseline metric and ends with the same metric measured again. No hand-waving on impact.