Services

Ithonga does one thing: we turn the repetitive, high-friction operations inside your business into autonomous workflows that run without you needing to hover over them. Everything below is a lens on that same job. Some engagements start with a small audit and grow. Others begin with a specific process a founder is tired of babysitting. Either way, the shape is the same — find the friction, design the fix, build it properly, and stay in the room after go-live.

Workflow Discovery Audit

The starting point for most engagements, and often a standalone piece of work. We spend time with your team to map how work actually moves through the business — where things queue up, where they get re-keyed between systems, where a person is doing what a workflow should. You get a written report ranking your candidate processes by two things: how much friction they carry today and how tractable they'd be to orchestrate. It's the piece of work that tells you where AI would genuinely earn its keep, and, just as usefully, where it wouldn't. If you decide to build with us afterwards, the audit feeds directly into the Design stage. If you don't, you still walk away with a clear operational picture.

Custom Agent Build

Once we know which workflow to tackle, we design and build the agent that runs it. That means specifying which decisions the agent is allowed to make, what it hands off to a person, which systems it reads from and writes to, and how it behaves when something upstream breaks. We build it as a production system rather than a demo — version-controlled, reviewable, and inspectable by your own team. Each build is scoped to a defined workflow with a defined outcome, so you know what you're getting before we start and what "done" looks like when we finish.

Integration and Deployment

An agent that can't reach your data or your tools is a party trick. Integration is where we wire the workflow into the systems you already run on — the CRM, the shared drive, the finance system, the ticket queue, whichever mix of Slack, Sheets, and internal apps your team actually lives in. Deployment is the cut-over: agreed go-live window, rollback plan, monitoring in place, and a named owner on both sides. We plan the switch carefully because production is where the interesting failure modes live, and we'd rather delay a go-live than let a workflow drift live before it's ready.

Managed Operation

A live workflow needs the same ongoing care as any other production system. Under a Managed Operation retainer, we monitor the workflow, alert on failures, run a monthly service review, and iterate as the surrounding business changes. Upstream vendors change APIs. Volumes shift. A team spots a use case that didn't exist on day one. Having the people who built the workflow stay close to it is what turns an initial go-live into a durable capability rather than another system that quietly rots. Every change is logged, so you always know what's different from last month and why.

Business Process Optimisation

Not every friction problem is best solved by adding an agent. Sometimes the workflow itself is the issue — too many hand-offs, unclear ownership, a step that only exists because a system limitation vanished three years ago. Business Process Optimisation is where we combine traditional process work with agent thinking: streamline the workflow first, then decide which parts benefit from automation and which parts should stay with a person. The output is a cleaner operation, a shorter cycle time, and a much clearer picture of where AI adds value rather than noise. It's often the right first move for teams that suspect they have a process problem, an AI problem, or both.

Task Automation

Not every problem needs a full multi-step workflow. Sometimes what a team really needs is one tedious, repeatable task quietly taken off their plate — a weekly report that gets compiled from four sources, an inbox triage that eats an hour every morning, a data-entry step between two systems that never quite justified a proper integration. Task Automation is the smaller cousin of Custom Agent Build: same discipline, tighter scope, faster to production. It's a good way to prove out the working relationship on a low-risk piece of work before committing to something larger, and it often surfaces the deeper workflow opportunities that turn into future engagements.

Agent Observability Retainer

A lighter-touch retainer than Managed Operation, for clients who have built — or had someone else build — their own agents and just want an independent set of eyes on how they're actually behaving in production. Includes monitoring setup, monthly performance review, drift and failure-mode reporting, and a quarterly recommendations note on what to fix, retire, or extend. A useful fit for teams with a first generation of AI experiments running quietly under-monitored, who want to know what's really happening before deciding what to do next.

Buy-vs-Build Advisory

A short, paid engagement — typically one to two weeks — helping you decide whether a specific business need is better solved by a bespoke agent, an off-the-shelf SaaS tool, or a hybrid. Includes a shortlist of viable vendors, an honest cost-and-lock-in comparison, and a written recommendation with rationale you can put in front of a co-founder or board. Sometimes the honest answer is "just buy it"; we'd rather say so and earn the trust than push you into a build that didn't need to happen.

In-house Team Enablement

A structured programme — a mix of workshops, pairing sessions, and reference builds — that lifts your own team to the point where they can maintain and extend the workflows we've delivered, or build their own. Deliverables include a curated internal playbook, code and prompt patterns adapted to your stack, and a defined graduation criterion so you know when your team is genuinely ready to run independently. Designed for organisations who want to own their AI capability rather than rent it long-term.

AI Vendor Due Diligence

A focused external review, on your behalf, of a specific AI vendor or platform you're considering procuring. Covers technical fit, integration effort, data-handling and residency posture, contract shape, and realistic total cost. Delivered as a written recommendation your procurement or leadership team can act on directly. A useful service for mid-market companies being asked to evaluate AI vendors faster than they've had time to build the muscle for.

Where to start

If you're not sure which of the above fits, start with a Discovery conversation. Fifteen to thirty minutes is usually enough for both of us to see whether there's a real fit and what the sensible first move would be. Book a Discovery conversation.