AI Development
AI Agent Development
We build AI agents that do more than chat: they can plan steps, call tools, and complete workflows across your product and internal systems. You get safe tool access, human approvals where needed, and an evaluation layer so quality is measurable—not vibes. Delivery aligned to Canada teams (CAD).
Overview
What this service is
An AI agent is a system that can decide what to do next, use tools (APIs), and execute multi-step tasks—while staying within strict safety and permission boundaries.
We design agent architecture (routing, memory/state, tool contracts, fallbacks) so outcomes are predictable and failure modes are visible.
Delivery includes instrumentation, evaluation tests, and handoff notes so your team can extend agents safely after launch.
Start Small
Start small in 7 days
Three pilot-friendly options that reduce risk and ship value fast. Choose one, share access, and we deliver a production-ready baseline.
Standard
AI delivery standard
Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.
Logging + tracing
Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.
Guardrails + safety
Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.
Evals + regression tests
Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.
Cost + latency controls
Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.
Documentation + handoff
Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.
Security-first integration
Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.
Benefits
What you get
Automate multi-step workflows (not just Q&A)
Reduce manual ops with approval-aware automation
Keep tool access safe with allowlists + RBAC
Measure quality with evals and regression tests
Control latency and cost with caching and routing
Ship with logs and incident-friendly observability
Features
What we deliver
Agent architecture + tool contracts
We define tool schemas, permissions, and error handling so the agent can act safely and consistently across systems.
Routing + intent handling
Route user requests to the right flows: Q&A, tool execution, escalation, or clarification—so the agent doesn’t guess.
Memory + state (session-safe)
Short-term state and optional user preferences stored safely with clear retention rules—no uncontrolled “memory”.
Human-in-the-loop approvals
Approval steps for risky actions (refunds, changes, deletes) with summaries and structured diffs for fast review.
Guardrails + safe fallbacks
Tool allowlists, refusal patterns, sensitive-data controls, and fallback behavior when confidence is low.
Evals + monitoring
Golden test sets, regression checks, traces, and KPI dashboards (success rate, tool errors, latency, cost) to keep quality improving.
Process
How we work
Discovery
Define jobs-to-be-done, tools, and risk boundaries.
Design
Agent routing, tool schemas, memory/state, and fallback plan.
Build
Implement flows, tool calls, guardrails, and UI/UX for agent interaction.
Evals
Create test sets, regression checks, and quality KPIs.
Launch
Monitoring, rollout plan, and handoff documentation.
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
Support agent that resolves tickets
Answer questions from docs, pull order/account state, and create/update tickets with structured fields when escalation is needed.
Ops agent for back-office actions
Run multi-step workflows like refunds/adjustments with approvals, audit logs, and safe action limits.
Sales / lead qualification agent
Qualify inbound leads, enrich context, route to the right owner, and schedule follow-ups with CRM updates.
Incident triage assistant
Summarize alerts, pull logs, propose hypotheses, and open investigation tasks—while keeping humans in control.
Internal knowledge + actions
Search SOPs and then execute actions: create tasks, update records, and generate status updates for teams.
AI Case Examples
Micro case studies (anonymous)
A few safe examples of outcomes we build for real operations—no client names, just results.
Secure Mobile Solution in Australian Defence Ecosystem
Problem: Secure data workflows were required in a regulated environment with strict access controls.
Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.
Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.
AI Knowledge Base Across 2,000+ Pages
Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.
Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.
Outcome: Reliable answers with <10s response times and measurable improvements on real queries.
Ops Automation with AI + n8n
Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.
Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.
Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.
Explore
Related solutions & technologies
Useful next pages if you’re planning an AI pilot or scaling this into a larger product.
Related solutions
FAQ
Frequently asked questions
A chatbot primarily answers questions. An agent can plan steps and use tools (APIs) to complete actions—like updating CRM fields, creating tickets, or triggering workflows—within strict safety boundaries.
Yes, when designed correctly. We implement tool allowlists, RBAC, approvals for risky actions, rate limits, and audit logs so access is controlled and reviewable.
We design low-confidence behavior: ask clarifying questions, return citations/sources, or escalate to a human with a structured summary.
Yes. We keep the system model-agnostic where possible and choose models based on accuracy, latency, and cost.
We create evaluation datasets, success criteria, and regression tests. We also monitor production metrics like completion rate, tool error rate, latency, and user feedback.
A list of tasks the agent should perform, the systems it must access, and your safety policy (what it can/can’t do without approval).
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Regional
Delivery considerations for your region
Compliance & Data (Canada)
For Canadian teams, we focus on practical privacy and security: least-privilege access, clear boundaries, and reviewable operational controls.
We can align implementation with SOC 2 / ISO-friendly practices (without claiming certification) and support documented data flows.
- SOC 2 / ISO-friendly patterns (no certification claims)
- Least-privilege access and secure session handling
- Retention/deletion and export flows where required
- PII-safe logging + access boundary documentation
- NDA and vendor onboarding docs on request
Timezone & Collaboration (North America)
We work with Canadian teams with North America overlap and meeting windows that fit your schedule.
Delivery stays predictable via weekly milestones, async updates, and clearly documented decisions.
- North America overlap and responsive communication
- Async-first updates with written scope decisions
- Weekly milestone demos and progress checkpoints
- Clear escalation path for blockers
- Tight change control with clear sign-offs
Engagement & Procurement (Canada)
We support procurement-friendly delivery: clear scope, change control, and billing cadence aligned to milestones when appropriate.
We can invoice in CAD for CAD-based engagements where required.
- CAD-based engagements and invoicing options
- Milestone-based billing and scope sign-offs
- Time-and-materials for evolving requirements
- Vendor onboarding pack on request
- Optional paid discovery to de-risk delivery
Security & Quality (North America)
We keep quality visible: clean PRs, reviewable changes, and test coverage that matches the risk of each feature.
Performance budgets and release discipline help maintain stability as the product scales.
- CI-friendly testing: unit + integration + smoke tests
- Performance budgets + bundle checks
- Structured release notes + rollback-safe deployments
- Security checklist for auth, roles, and data flows
- Observability hooks (logs + error tracking) ready for production
Want help with AI agent development?
Get a clear plan for Canada teams—scope, timeline, and next steps. CAD-based engagements.
Reply within 2 hours. No-pressure consultation.