AI agents that actually work. In production.
Tool-using agents on Claude and GPT — with RAG, evals, guardrails, observability, and human-in-the-loop where it matters. Built by a Vancouver, BC team shipping production AI, not demos. Discovery from $3,500, builds from $9,000.
What you walk away with
A production agent — not a Notebook your CTO has to keep alive on weekends.
Workflows the team stops doing
Customer support triage, order ops, lead qualification, internal Q&A, content drafting — wired to the same tools your team uses today.
Evals-driven quality
Every agent ships with a written eval suite. Quality is a number we track per release — not vibes after a demo.
Guardrails by default
Tool-allow-listing, input/output filters, prompt-injection defense, audit logs. Production AI that survives an enterprise review.
Tools wired in correctly
Stripe, Shopify, HubSpot, Slack, Postgres, your APIs. Real tool use, not pretend — with retries and idempotency keys.
Human-in-the-loop where it matters
Refunds over $500, customer escalations, anything irreversible — gated for human approval, with a Slack-style review UI.
Observability you trust
Token usage, latency, cost-per-task, success rate, error tags. Dashboards that answer 'is the agent good today?' in one glance.
Three workflow patterns we ship most often.
Customer-facing, internal ops, and revenue-side. Each one has the same anatomy — only the tools and rubrics change.
Customer support
Tier-1 deflection without trashing the brand.
- Triages and answers Tier-1 tickets (RAG over your docs)
- Issues refunds, status updates, order lookups
- Escalates to humans with full context
- iOS / Android / web / Slack / email surfaces
- Evals against your past resolved tickets
Best for: DTC, SaaS, marketplaces with high Tier-1 ticket volume and clear escalation rules.
Internal ops
The work your team does between Slack messages.
- Order review, inventory rebalancing, refund triage
- Cross-system data reconciliation
- PR/change-request reviewers for low-risk merges
- Internal Q&A over wikis + tickets + Slack history
- Slack-native interface with human-in-loop gates
Best for: Ops-heavy companies (retail, fintech, healthcare-ops, logistics) drowning in repetitive internal work.
Sales + marketing
The pipeline your reps wish they had time for.
- Lead enrichment + qualification at scale
- Personalized outbound (without sounding like AI)
- RFP / discovery-call summarization
- CRM hygiene — dedupe, enrich, route
- Daily-stand-up briefings for revenue leaders
Best for: B2B SaaS and services teams with named-account motions and tight rep capacity.
Don't see your workflow? The discovery audit ($3,500) maps any candidate workflow against feasibility, eval design, and tool wiring before any code gets written.
Five things every production agent needs
The difference between a Friday-night ChatGPT demo and an agent your CFO is comfortable putting in front of customers.
Trigger
An event fires the agent: a new ticket, a webhook, a cron, a Slack message, an API call. The agent's scope is defined by the trigger.
Reasoning loop
The model plans, picks tools, executes them, observes results, and repeats until the task is done — bounded by step + token + cost limits.
Tool calls
Real APIs: Stripe, Shopify, your Postgres, your internal endpoints. Typed schemas, retries, idempotency keys, and audit logs on every call.
Guardrails + human-in-loop
Allow-list of tools, output filters, prompt-injection defenses. Irreversible actions gate for human approval via Slack or your admin UI.
Evals
Every release runs against a versioned eval suite. Quality is a metric, not a hunch. Regressions block deploys, full stop.
Eight surfaces, one production system
Everything we ship on a typical Build — and what the Care retainer keeps alive after launch.
Tool-using agents on Claude or GPT
Model-agnostic prompt programs, structured outputs, function calling, multi-step reasoning — picked per task on cost × quality.
Retrieval (RAG)
Hybrid retrieval over your docs, tickets, code, or product catalog. Indexed in pgvector, Pinecone, or Turbopuffer — picked for your latency + cost.
Tool wiring
Stripe, Shopify, HubSpot, Postgres, your APIs. Typed schemas, retries, audit logs. Real production plumbing.
Evals + regression suites
Golden datasets, LLM-as-judge where useful, deterministic asserts elsewhere. Quality tracked over releases.
Guardrails + safety
Tool-allow-list, output filters, prompt-injection defenses, jailbreak resistance. Auditable.
Human-in-the-loop
Slack-native approval UI for irreversible actions. Reviewers see context + reasoning + tool calls.
Orchestration + durability
Inngest, Temporal, or Mastra for long-running flows. Crash-safe steps, retries, observability across runs.
Observability + cost
LangSmith / Helicone / OpenTelemetry. Token spend, latency, success rate, error tags — all on the dashboard.
What makes an agent safe to put in production
A demo passes once. A production agent passes every release. The discipline below is the difference.
Golden datasets
Evals
LLM-as-judge rubrics
Evals
Deterministic asserts
Evals
Regression dashboards
Evals
Tool allow-list
Safety
Output filters
Safety
Prompt-injection defenses
Safety
Human-in-loop gates
Safety
Audit log + replay
Observability
Cost + latency dashboards
Observability
Shadow-mode rollouts
Rollout
Canary + auto-rollback
Rollout
How we ship agents that don't embarrass you
Evals-first. Shadow before cutover. Maintenance built in.
Discover
Workflow audit, candidate task selection, eval rubric design, scoping doc. The discovery audit ($3,500) ends with a go / no-go recommendation.
Eval-first build
Golden dataset before code. Prompt program, tool wiring, retrieval, guardrails — each shipped against the eval suite, not against vibes.
Shadow + canary
Run alongside the human workflow before fully replacing it. Compare outcomes, tune evals, then canary, then full rollout with auto-rollback.
Maintain
Monthly eval re-runs as models change, drift detection, new tools as the workflow expands. Optional Care retainer keeps it sharp.
No-code agents vs. custom-built agents
No-code is amazing for prototyping. For anything in front of customers or money, the gap shows up fast.
Start with Discovery. Build the agent. Keep it sharp.
One-time builds with optional Care retainer. No annual lock-ins.
Start here
Discovery Audit · $3,500
2-week deep-dive on candidate workflows, eval rubric design, and a go / no-go build recommendation. Cost credits back against the first month of any Build.
Starter
One agent, one workflow, one or two tools. Real production-grade.
- 1 agent on Claude or GPT
- 1-2 tool integrations (REST / Stripe / Shopify / etc.)
- Eval suite (~50 golden cases)
- Slack-native human-in-loop gate
- 30-day post-launch warranty
Teams testing AI on a contained workflow with clear success metrics.
Growth
Multi-step workflow or multi-agent system with RAG and evals.
- Multi-step / multi-agent orchestration (Mastra / Inngest)
- RAG over your docs / tickets / catalog
- 3-5 tool integrations
- Eval suite (~250 cases) + LLM-as-judge rubrics
- Observability dashboard (LangSmith / Helicone)
- 90-day post-launch support
The most common shape: a workflow worth $50K-$500K/yr in labor or revenue.
Scale
Mission-critical agents: multi-tenant, multi-model, full evals + ops.
- Multi-tenant + multi-model routing
- Fine-tuning or evals-driven prompt programs
- Custom RAG architecture (hybrid retrieval)
- Full observability + cost guardrails + canary
- Compliance-friendly audit log + replay
- 6-month support + ops team training
Enterprise, regulated industries, agents in front of paying customers at scale.
Optional · Care Retainer · $1,500/mo
Monthly eval re-runs as models change, drift detection, prompt + model updates, observability tuning, minor feature additions. Month-to-month after launch.
All prices in USD. Model usage (tokens) billed separately at cost, with a per-task ceiling. Payment 50% to start, 50% at launch.
Built on a modern AI stack
Best-of-breed tools across models, orchestration, retrieval, evals, and observability — picked for the workload.
Questions, answered
What founders, CTOs, and ops leads actually ask about putting agents in production.
Have a workflow your team would love to hand off?
Book a free 30-minute discovery call. We'll walk through the workflow and tell you honestly whether an agent is the right tool — or whether it's a normal-software problem in disguise.
Book a discovery call