AI Agents Portfolio

Agents that complete work rather than describe it — each one scoped to a single job, bounded by explicit guardrails, and logged end to end.

  • Tool Use On Real Systems
  • Approval Gates
  • Full Run Traces
  • Reversible Actions
  • Evaluation Suites

Selected work

AI Agents We Have Deployed

Agents that hold context, use real tools and take action — not prompts wrapped in a chat window.

Voice Booking Agent — Dental Appointments by Phone
01 Voice AI

Voice Booking Agent, Dental Appointments by Phone

A voice agent that answers the practice phone, understands natural speech, checks live availability and books the appointment before hanging up.

  • Gemini
  • Voice
  • Calendar
Gmail Email Manager — Triage, Draft & Label
02 Productivity

Gmail Email Manager, Triage, Draft & Label

An inbox agent that reads, categorises and labels incoming mail, drafts contextual replies and surfaces only what genuinely needs a human decision.

  • Gmail
  • Triage
  • Drafting
Personal Life Manager — Voice-Enabled Telegram Agent
03 Personal Productivity

Personal Life Manager, Voice-Enabled Telegram Agent

A personal agent reachable by voice or text on Telegram, managing calendar, tasks, notes and email across connected Google services.

  • Telegram
  • Voice
  • Google Workspace
Store Operations Agent — WooCommerce via Telegram
04 E-commerce

Store Operations Agent, WooCommerce via Telegram

An operations agent running store admin from a chat thread — order lookups, stock changes and customer queries without opening the dashboard.

  • WooCommerce
  • OpenRouter
  • Telegram
Database Query Agent — Ask Your Data in Plain English
05 Data & BI

Database Query Agent, Ask Your Data in Plain English

An agent that translates plain-English questions into safe, schema-aware queries and returns explained results to non-technical staff.

  • SQL
  • RAG
  • Analytics
AI Confidence Coach — Guided Coaching Programme
06 Coaching

AI Confidence Coach, Guided Coaching Programme

A structured coaching agent running a multi-session programme, tracking each participant’s progress and following up by email between sessions.

  • GPT-4o
  • Sheets
  • Gmail

A selection of ai agents work. Detailed case studies, metrics and references are shared on request.

Methodology

Our Approach

The methodology behind every engagement, from first workshop to the retainer that follows launch.

  1. 01

    Task Definition

    One job, defined precisely: what counts as done, what must never happen, and which cases always belong to a person.

  2. 02

    Tool & Guardrail Design

    The narrow function set the agent may call, the value and volume limits around it, and the approval gates on anything consequential.

  3. 03

    Build & Instrument

    Built with structured tracing from the first commit, so every plan and tool call is inspectable while it is still being developed.

  4. 04

    Evaluation

    Scored against real historical cases with known correct outcomes, including the adversarial ones you would not want it to get wrong.

  5. 05

    Supervised Run

    It proposes, a person approves, and we measure the agreement rate until the boundary is proven against your own data.

  6. 06

    Autonomy & Monitor

    Gates relax only where evidence supports it, with alerting, spend limits and a kill switch left permanently in place.

Common challenges

Ready To Hand Something Over?

The problems clients usually arrive with — and how each one gets handled.

  • How do we stop it doing damage?

    Narrow toolsets rather than open access, approval gates on destructive operations, value and volume caps per run and per day, and actions built to be reversible.

  • How do we know it works?

    It is scored against historical cases where the right outcome is already known, then runs supervised until the agreement rate justifies relaxing a gate.

  • Is an agent even the right tool?

    Often not. Deterministic processes are cheaper and easier to reason about as plain automation, and we will say so rather than putting a model where an if-statement belongs.

  • What will it cost to run?

    Smaller models where they suffice, caching on repeated context and hard spend caps per agent — with cost per completed task reported alongside accuracy.

  • Can we explain a decision later?

    Every run stores its plan, tool calls, inputs and outputs, so any outcome can be replayed and explained to a customer, an auditor or a post-mortem.

Which Task Would You Hand Over First?

Name the process that eats your team’s week. We will scope it, define the boundary and show you what an agent can safely own.