Services
AI agents and conversational AI
A conversational system that answers fluently but wrongly is worse than no system, because it fails with confidence and at scale. Corpshore Canada designs and delivers conversational AI and agent systems, including bilingual assistants that handle Canadian French correctly, from an AI practice ranked fifth of fifty AI outsourcing companies worldwide by Outsource Accelerator. Systems are built with clear boundaries on what they decide and what they escalate, and with contact centre quality assurance applied to their output rather than a launch and a hope. We come at this from both sides, as a bilingual Canadian contact centre operator and as an AI practice, so an agent is designed to hand off cleanly to a human and to be measured on resolution rather than deflection. The Canadian French capability is the same one the data pillar builds, matched by variety, because a Quebec customer identifies a European French or translated assistant within a few sentences.
How the service works
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Use case scoping and containment design
We scope what the agent should handle and, just as important, what it should not, and we design the containment and escalation before the conversation flows. An agent measured on deflection learns to trap customers, so we design for clean resolution and a fast handoff to a person instead.
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Build with grounding and boundaries
We build the agent grounded in your knowledge and systems, with retrieval where it needs current facts, and explicit boundaries on the actions it can take. Where an agent can act, the action is logged, explainable and reversible, and anything consequential routes to a human rather than being executed on a confident guess.
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Bilingual quality assurance
Agent output is reviewed with the same contact centre quality framework we apply to human agents, in English and in Canadian French by French-first quality staff. Conversations are scored, failure patterns are found and the grounding and prompts are corrected, because an untested conversational surface degrades quietly and in public.
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Launch, monitoring and human handoff
Systems launch with monitoring for containment, escalation and customer satisfaction, and with a human handoff that carries the full context so the customer does not repeat themselves. We tune against real conversations, and we watch resolution and satisfaction rather than a raw deflection number that can hide a poor experience.
How we deliver it from Canada
Delivery is from Canada, with conversation designers, engineers and bilingual quality staff in Ontario, Quebec and Alberta. Canadian French is a first-class capability matched by variety, and human escalation can route into a bilingual Canadian contact centre under the same governance where the client wants a single accountable line. Data residency is configured to your requirement including Canadian-only where a public sector buyer asks, and every deployment carries a governance and consent chain under Canadian privacy law.
Pilot, single use case
A conversation designer, an engineer and a quality reviewer building and testing a contained single-use-case assistant with a designed escalation path before it goes live.
Programme, multi-channel assistant
A team across conversation design, engineering and bilingual quality assurance delivering an assistant across voice and non-voice channels, with monitoring and human handoff.
Practice, agents plus contact centre
A standing practice combining conversational systems with a bilingual Canadian contact centre for escalation, under one governance framework where the client wants AI and human handling in a single line.
Compliance and data handling
Conversational systems are governed under PIPEDA and, where Quebec residents' data is in scope, Law 25, including its automated-decision provisions where an agent makes or materially supports a decision about a person, and its transparency expectation that a user can know they are dealing with a system. Consequential actions route to a human, every agent action is logged, and the escalation path is the review-by-a-person mechanism the regime expects. Data residency and handling follow your requirement and the relevant group security framework.
Technology
We work across conversational and agent frameworks, retrieval systems for grounding, and the model providers a use case needs, integrated with your knowledge base, CRM and contact centre tooling rather than bolted on beside them. Specific platform choices are made with you against the use case, the channel mix and the residency requirement rather than prescribed here, and quality tooling captures conversation scoring and escalation as first-class outputs.
How performance is measured
- Containment and resolution rate, separated from raw deflection
- Escalation accuracy and handoff quality to a human
- Customer satisfaction on agent-handled conversations, by language
- Grounding accuracy and rate of unsupported or incorrect answers
- Action reversal rate where the agent can act
Reporting separates resolution from deflection, because an agent that traps customers can post a flattering deflection number while destroying the experience. We report containment, escalation quality and customer satisfaction by language, with Canadian French performance shown separately so a gap cannot hide inside a blended figure. Governance runs on an agreed cadence with the analysis prepared by us.
Where this applies
Technology and SaaS
Bilingual support and onboarding assistants grounded in product knowledge, with clean escalation to a human and quality assurance applied to every conversation.
Insurance
Policy and claims assistants that answer and guide but route any coverage or settlement question to a person, with every action logged and reversible.
Banking and financial services
Servicing assistants with strict action boundaries, human review on anything consequential and a full audit trail a risk committee can inspect.
Pricing and engagement models
Conversational and agent work is priced as a fixed-scope pilot, a defined build, or a build followed by a managed operation that can include human escalation into a Canadian contact centre. The pilot proves containment and quality on one use case, the build delivers the production assistant, and the managed operation runs and improves it where the conversational surface has to be maintained and staffed for handoff.
Frequently asked questions
Can your assistants handle Canadian French properly?
Yes, and it is a core reason buyers choose us. The Canadian French capability is the same one the data pillar builds, matched across Quebec, Acadian, Franco-Ontarian and western francophone varieties, because a Quebec customer identifies a European French or translated assistant within a few sentences. Bilingual quality staff review the French output rather than trusting a translation.
How do you stop an agent from answering confidently but wrongly?
We ground the agent in your knowledge and systems, use retrieval for current facts, and set explicit boundaries on what it answers and what it escalates. Output is scored with a contact centre quality framework, unsupported answers are treated as failures to fix, and anything consequential routes to a human rather than being executed on a confident guess.
Why do you measure resolution rather than deflection?
Because deflection can be gamed. An agent measured on deflection learns to trap customers and can post a flattering number while ruining the experience. We measure containment, resolution and customer satisfaction, separated by language, so a system that avoids handoffs at the cost of the customer shows up as the problem it is rather than a success.
What happens when the agent cannot help?
It hands off to a person cleanly, carrying the full conversation context so the customer does not repeat themselves. We design the escalation path before the conversation flows, and where the client wants it the handoff routes into a bilingual Canadian contact centre under the same governance, so AI and human handling sit in one accountable line rather than two.
Can the agent take actions, not just answer?
Yes, within explicit boundaries. Where an agent can act, each action is logged, explainable and reversible, and anything consequential routes to a human for review rather than being executed autonomously. That boundary design, rather than the model, is what determines whether an acting agent is safe to put in front of real customers and real systems.
How are conversational systems governed under Canadian law?
Under PIPEDA and, where Quebec residents' data is in scope, Law 25, including its automated-decision provisions where an agent materially supports a decision, and its expectation that a user can know they are dealing with a system. The escalation path is the review-by-a-person mechanism, actions are logged, and data residency is configured to your requirement including Canadian-only.
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