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AI Agent Development

Agents that hold up in production.

Custom AI agents for a defined job in your existing systems. We agree the inputs, approval rules and success measure, then build and test one workflow at a fixed price.

Book a consult →See what the build includes

BDC

Preferred vendor

A preferred AI vendor for Business Development Bank of Canada advisory clients.

LIFT’s digital transformation and AI stream offers eligible Canadian businesses $25,000 to $2M in financing. Technology must come from a Canadian supplier or integrator. We are one.

How LIFT works

The short version

Define the job before the build.

Gartner expects over 40 percent of agent projects to be canceled by the end of 2027, citing cost, unclear value and weak risk controls. Our first two weeks address scope, measurement and review requirements before development begins.

One workflow, with a written finish line.
One person who measures it.
A written point where a miss stops the pilot.
The security review answered before the build.

If you have not yet decided what to build, start with AI consulting. We estimate that our own agents save 50 or more team hours a week. A public server at mcp.strataigize.com lets an agent query our business.

Strataigize Marketing40+Estimated client tasks queued monthlyRead the case study →

What we build

Custom AI agents, by the job.

Every one of these is scoped as a single bounded workflow first. The system comes from stacking proven workflows. Each is described in full, with its build steps and price, in the catalogue of eleven AI systems we build.

Intake and qualification agents

Inbound leads, applications, or requests read, enriched, qualified against your rules, and routed or booked. The judgment calls stay with a person; the sorting does not.

Reporting and analysis agents

Pull from your ad platforms, CRM, and analytics on a schedule, surface what changed and what it means, and write the next actions into the tool your team already uses.

Document and back-office agents

Invoices, contracts, forms, and tickets read and turned into structured records in your systems, with exceptions escalated instead of guessed at.

Research and monitoring agents

Competitors, pricing, regulation, or your own accounts watched continuously, distilled into a short daily read.

Internal knowledge agents

An agent that answers from your documents, your policies, and your history, with citations back to the source so an answer can be checked.

Agent-callable surfaces

MCP servers, tool APIs, and machine-readable endpoints so your systems, and your customers’ AI assistants, can call your business directly. We run one ourselves.

How it works

The engagement, in order.

Scope one workflow

A working session on your actual process. We pick the single highest-value bounded workflow and name the ones you should not automate yet.

Agree the numbers

Fixed price for the first workflow, one written success metric, a named person who measures it, and a kill threshold that stops the project. All before any build.

Clear procurement

Security questionnaire, data flow, subprocessors, and DPA handled in week zero. Our posture is already published, so your reviewer starts reading immediately.

Build and shadow

The agent runs on your real data and takes no irreversible action. Every output is reviewed, and the disagreements tune it. You measure accuracy before you measure time saved.

Go live, supervised

The agent runs within the agreed permissions, with a person approving irreversible actions. Your team can read the logs and review performance before changing that scope.

Decide, then expand

At the end of the pilot: expand, extend once with a specific fix, or stop. Written in advance. Workflows two and three are priced before the first one proves out.

The box

What the first build includes.

One workflow, a success line, and a written point where a miss stops the pilot.
A trial run on your data, then a supervised go-live.
You own the prompts and the code.

The full list is in what an AI agent build actually includes. We estimate that our own agents reclaim 50 or more hours a week. The public server listed eight tools on 13 September 2026. No outside client had called it in the week to 6 September.

Procurement

Your security review, answered already.

The security questionnaire often arrives in week five. Ours is already public.

Trust and security covers how client data is handled, our subprocessors, and a data processing agreement on request.
The AI governance summary follows the four functions of the NIST AI Risk Management Framework.
We do not hold SOC 2, and the trust page says so.
Access is granted by you, and you can revoke it.

Before you talk to anyone, including us, take the checklist: 24 questions to ask an AI agent vendor. Still deciding whether to use a vendor at all? Start with build versus buy, then the pilot structure that survives procurement.

The ongoing layer is AI workflow automation. It maintains and expands the agents month over month.

Case studies

Agents in production, documented.

Strataigize Marketing

How Our Marketing Agency Uses AI Agents to Automate Busywork

40+ Estimated client tasks queued monthly7 days A week of industry news, read in minutes daily

Read the case study →

Strataigize Marketing

Our AI Productivity Journey: Research & Case Study

+25% Quality uplift in the UK AISI workplace trial4+ hrs Saved weekly by heavy users, US Fed survey

Read the case study →

Browse every case study →

Questions

AI agent development, answered.

What does an AI agent development company do?

It designs, builds, integrates, and maintains AI agents that complete a job end to end inside your existing systems, rather than selling you a chatbot or a subscription. The work is mostly integration, data handling, and governance; the model itself is the smallest part. Strataigize builds them human-in-the-loop, so a person approves anything irreversible.

How long does it take to build an AI agent?

Our pilots run 30 to 90 days, because shadow mode on your real data and a supervised go-live are part of the scope. A simple single-workflow automation can be built in two to six weeks including integration and testing. Multi-workflow builds run a quarter, delivered in phases. Anyone promising a production multi-system agent in a week is skipping the testing you will pay for later.

Do we own the agent, the prompts, and the code?

Yes. You own the prompts, the code, the configuration and the evaluation set, and you can export them. Those ownership terms are part of the contract.

Are you SOC 2 certified?

No. Our trust and security page describes the controls we operate: least-privilege client-granted access, credentials in managed stores, an AI governance summary aligned to the NIST AI Risk Management Framework, our subprocessor list, and a DPA on request. We complete vendor security questionnaires on request.

Should we hire AI agent developers or use an agency?

Hire in-house when the workflow is core to how you compete and you can name the engineer who owns it in month nine. Use an outside team when you want it built once, correctly, with the maintenance covered. MIT research in 2025 found external partnerships succeeded about twice as often as pure in-house AI builds.

Which industries do you build agents for?

Service businesses, SaaS, mobile app companies, and enterprise marketing and operations teams across the US and Canada. The common thread is a repetitive, rules-heavy workflow that touches several systems and currently eats senior hours.

Which agencies help enterprise teams deploy AI marketing automation?

We start enterprise work the same way we start a ten-person shop: one workflow, a success metric, and the security answers in week zero. We do not hold SOC 2, and we say so on the trust page.