We build AI that survives production.
Most AI projects stop at an impressive demo and never reach real use. We build the agent and the infrastructure that keeps it running, with a clean handoff to a person whenever it's unsure, and a record of every decision it makes.
Why most AI projects never get used
Almost every buyer in this market has been burned the same way, at least once.
A demo that never goes live
It impresses everyone in the meeting. Then no one built the path to actually put it in front of real customers, so it never does.
An agent nobody's watching
It works in the demo, then quietly starts making the wrong call in production. Without monitoring and an easy way to hand off to a person, no one notices until a customer does.
Data that isn't ready
The AI itself is rarely the hard part. Getting your data organized and flowing reliably is where most projects actually get stuck.
Seven ways we can help
Each one is a scoped piece of work with a fixed timeline. Click any card for what it involves and what you get.
AI agents & workflow automation
AI agents that carry out one real, repeated task in your business, not a chatbot demo. Built around a single workflow, with monitoring and an easy way to pause it if it gets something wrong.
AI assistant for your own documents
An AI assistant that answers questions from your own documents and data, and shows you exactly where each answer came from. This approach is often called RAG (retrieval-augmented generation), built for accuracy you can check, not just a demo.
Machine learning & forecasting models
Models that predict what your business needs to plan around: demand, load, risk. Stated as a realistic range, not one number you're tempted to treat as certain.
Getting AI live, and keeping it working
The part most AI vendors skip, sometimes called MLOps: getting a model into real use, watching it, retraining it, and building a path that survives past the first demo.
Data platforms & pipelines
Pulling your data together, cleaning it up, and storing it somewhere useful, sized to what you actually need, not an oversized system built for a scale you don't have.
AI voice & conversational agents
Voice and chat agents that handle real call and message volume (qualifying leads, booking appointments, basic support), with a clean handoff to a person the moment the conversation actually needs one.
AI opportunity audit
A two-week, fixed-price review of your data, your goals, and what you already have in place: a scored readout and a concrete starting point, not a slide deck of ambitions.
Real clients, real results
One real, verifiable number per project. If a project doesn't have one yet, it isn't here.
The chatbot they asked for, and the rulebase it needed first
A consultancy asked us for a chatbot to answer eligibility questions. Their rules weren't written down in one place, so we built that first. The assistant now answers only from the official rules, and shows which rule it used and when that rule was in force, including for past cases.
A two-week AI audit that recommended against most of it
Self-calibrating obstacle detection for a manufacturing line
The retrieval pipeline behind an AI agent platform's knowledge base
What our clients say
“They rebuilt our whole rulebase before touching the chatbot we asked for, which turned out to be exactly the right call. We can now answer for any past decision, on the exact rules that applied that day.”
Read the case study →“False alarms were the reason plants kept switching the device off. The team treated that as the actual problem to solve, not just a model to tune, and it shows in how the calibration holds up on lines it's never seen.”
Read the case study →“Citation accuracy on tables and clauses was our weak point before this. They rebuilt the pipeline around exactly that failure mode and slotted it into a live product without disrupting the rest of the team.”
Read the case study →How a project runs
Most projects take three to six weeks, at one price agreed before we start.
Scope agreed, something already working
We confirm the scope, the data we need, and what success looks like, in writing, before any building starts. By the end of week one you see something real running, not a plan.
Built against your real data
Work moves from a sample to your actual systems. A short check-in each week, usually 20 minutes, on what shipped, what we found, and what changes next.
Tested, monitored, handed over
We test against data it hasn't seen before. Monitoring and alerts go in before launch, not after. Handover includes documentation a future engineer can follow.
Two disciplines, one team
Forecasta pairs deep AI modelling expertise with senior production-infrastructure experience on every project, one continuous thread of ownership, not a handoff between teams.
Why two disciplines
Most AI companies are good at one half of the job. Some build good models but can't ship reliable systems; others ship reliable systems but outsource the modelling. We built Forecasta to close that gap.
Only two projects at a time
Ten to twenty hours a week of senior time, and nothing more. That limit is why nobody junior touches your project, and why we're honest about scope instead of promising more than we can deliver.
Where we are
A Canadian company, working remotely with teams across North America and the UK, with a weekly check-in and direct access to whatever we're building as we build it.
- Open-ended work with no defined scope
- Models with no realistic path into actual use
- Billing by the hour
Common questions
How much does this cost?
Every project is one fixed price for one fixed scope, agreed in writing before we start. We do not bill hourly. The number depends on what you're building, so we quote it after a short scoping call rather than publishing a range that would be wrong for most people.
How long does a project take?
Most projects run 3–6 weeks. You see something real and working by the end of week one, not just a plan.
What do you need from us?
Access to the relevant data and systems, and one point of contact who can answer questions within a day. That's it. We don't need a dedicated project manager on your side.
What if the scope changes partway through?
We tell you right away, with the cost and timeline impact stated plainly, and agree the change before continuing. We don't quietly absorb extra work, and we don't spring a surprise invoice on you at the end.
Do you work with our existing stack?
Usually, yes. We build around what you already have rather than replacing it wholesale, and we'll say upfront if something doesn't fit.
Who owns the code and the model?
You do. Everything we build (code, trained models, documentation) is yours outright at handover.
Are you based in Toronto?
We're a Canadian company, working remotely with teams across North America and the UK.
Have a project you want built properly?
Tell us what you're trying to do and we'll tell you honestly whether it's a fit: for a project, or for the audit first.
Or email info@forecasta.ai. We usually reply within one business day.
A free check on how ready you are for AI
Ten questions across your data, how clear the goal is, your systems, and who'd own it. Scored, not guessed. No email required.