Agentic AI development in Abbotsford
Move from an assistant that talks to one that gets things done.
Agentic AI development turns a chat assistant into software that plans, uses your tools, remembers what it learned and checks its own work. We help you choose which jobs deserve that freedom, and which are safer left to a person or a fixed rule.
Free audit, no obligation · In-house team since 2015 · Abbotsford studio
Common doubts about agentic AI and how we address them
Agentic AI sounds exciting and slightly alarming at once. These are the doubts worth taking seriously, followed by the steps we take and the difference you notice.
- 01
“Our chat assistant talks nicely but never finishes anything.”
WHAT WE DOWe list the tasks a person does after the chat ends, such as looking up an order or filing a form, and give the assistant narrowly scoped tools to do each one, starting with read-only ones.WHAT CHANGESThe conversation ends with work completed, and the first tools carry little risk. - 02
“I can't tell which agent promises are real and which are noise.”
WHAT WE DOWe explain the main ingredients in plain words: planning, tool use, memory and self-checking. Then we test each on a small task of yours, so you see which ingredients actually matter for your work.WHAT CHANGESYou judge the idea on a demonstration with your own work, not on buzzwords. - 03
“Giving software more freedom feels like a bet I can't take back.”
WHAT WE DOFreedom is added in stages. The agent starts by suggesting, then acts with approval, and only later acts alone on steps that have proven dull and safe. You can pull it back any time.WHAT CHANGESTrust grows from what you have watched it do, and every grant can be reversed. - 04
“I'm not sure which of our jobs even suit an agent.”
WHAT WE DOWe score each candidate job on how messy its input is, how costly a wrong answer would be and how easily a person can check the result. Jobs that fail the test stay with traditional software or with staff.WHAT CHANGESYou get an honest shortlist, including the jobs where an agent is the wrong tool.
Chatting is easy; finishing the work is the hard part.
A chat assistant can answer a question and stop. Agentic AI goes further: given a goal, it plans the steps, picks a tool, acts, looks at the result and tries again if it missed. Four ingredients make that possible, namely planning, tool use, memory and self-checking. Each one adds capability, and each one adds a way to go wrong, which is why we introduce them one at a time.
For a valley business the useful question is where to allow that freedom. A task with messy wording, costly delays and an easily checked result is a good candidate. A task that moves money or changes official records usually belongs in traditional software, with an agent preparing the work and a person approving it.
- People copy chat answers into other systems by hand
- Your assistant replies but never completes a task
- You cannot tell which jobs an agent suits
What agentic AI development brings to a working business
How things look once the marketing is done right.
- 01
Planning instead of scripts
Given a goal, an agentic system breaks it into steps and adjusts when something unexpected turns up, which a fixed script cannot do.
- 02
Tools it can actually use
Looking up a record, drafting a reply or filing a form becomes part of the same task, so the assistant produces finished work and not only text.
- 03
Memory of what matters
Notes about a customer, a job or an earlier decision are kept where the agent can find them, so people stop repeating themselves.
- 04
Checks before it reports back
The agent compares its draft with your rules and sources, then marks what it is unsure of. Self-checking catches some errors; a person still reviews what matters.
What is included in agentic AI development
- 01Chat-to-action job audit
- 02Tool and data connections
- 03Memory and notes design
- 04Planning and self-check rules
- 05Approval levels by risk
- 06Testing on real requests
- 07Usage cost estimate and caps
- 08Conversation and action logs
The tools in our toolkit.
- OpenAI API
- Claude
- LangGraph
- Model Context Protocol
- Python
- Node.js
- 01Fixed-scope projectScope, schedule and price set up front. Suits MVPs, websites and builds with clear requirements.
- 02Dedicated teamDevelopers, designers and testers join your team on a monthly arrangement.
- 03Support retainerRegular upkeep, upgrades and improvements, with response times agreed in advance.
Our Agentic AI process, step by step
- 01
Discover
We sit down with you to learn your goals, customers and limits, then hand back a written scope and estimate.
- 02
Design
Screen flows, wireframes and clickable mockups get tested with real users before any code is written.
- 03
Build & test
Two-week build cycles that end in a working demo, backed by code reviews and automated tests.
- 04
Launch & support
A phased launch, live monitoring, team training and support that continues as you grow.
What clients say
“Our Google Ads campaigns were burning through budget with little to show for it. All In One Marketing Pro stepped in and completely revamped our strategy, targeting the right audience and optimizing our ads for conversions and our website also google map. Within three months, our cost per lead dropped by 65%, and our ROI improved significantly. They solved a problem we thought was unsolvable! Thank you so much Lovi and all in one marketing team”
Alissa Mandzuk-PowerClient review “We had no real strategy for social media before, but after working with All In One Marketing Pro, our engagement skyrocketed! Our Instagram and Facebook pages grew by over 150%, and we’re now getting consistent leads directly from social media. Their content is top-notch, and they truly understand how to turn followers into customers.”
N KaurClient review “All in One Marketing has played a crucial role in the growth of my cardiology practice. Their targeted strategies have greatly enhanced patient engagement through social media, and by the second month of running Google Ads, we began seeing a steady influx of new patients. They are highly professional and results-driven! Thank you”
Emma NClient review
Each review is quoted as the client wrote it. Results depend on your market, your budget and where you start.
An agentic AI plans a sequence of steps toward a goal, uses tools to carry them out, keeps useful notes and checks its own output, while a chatbot only replies. The difference is freedom to act, not intelligence. That freedom is also the risk, so each ability is switched on gradually, with permissions that match the task.
Use traditional software when the rules are known and the answer must be identical every time, and an agent when the input is messy language or the cases vary. Payroll, stock counts and invoices belong with fixed rules. Sorting a shared inbox or drafting replies suits an agent. Many good systems combine both, with the agent reading and the software recording.
It is too risky wherever a wrong action is costly or hard to undo and nobody reviews it, such as paying suppliers, changing prices or deleting customer records. In those places the agent drafts and a person approves. Private data needs extra care under PIPEDA and BC's PIPA, and we work alongside your lawyer on that.
You need a clear job, written examples of good and bad outcomes, access to the tools involved, and one person accountable for the result. The documents and records the agent will read should be reasonably tidy. If they are not, we start there, because an agent built on messy data only produces confident mistakes faster.