Engineering firms
Engineers lose hours finding the right clause in standards, specifications and past project files.
- Specification search across approved documents
- Document checking against the specification
- Proposal preparation from past bids
AI workflows fail when the people building them never see the work. Our Forward-Deployed Engineers sit with the teams who run the process.
We run discovery interviews and workflow observation in person, on site in Johannesburg, Pretoria, Cape Town and Durban.
Data handling is reviewed with your security, legal and POPIA teams before anything is launched.
Engineers work South African business hours, so reviews, demos and fixes happen in your day.
If your operations extend beyond South Africa, we deliver remotely, with planned site visits for discovery and launch.
We focus on South African engineering, mining and agriculture, where expert knowledge is scarce and documents are long. These are typical first workflows.
Engineers lose hours finding the right clause in standards, specifications and past project files.
Maintenance knowledge sits with a few experienced people and in manuals nobody has time to read.
Field teams and customers ask the same questions, and the answers live in research and product documents.
We measure the result in terms your teams already track: time per deliverable, cycle time, rework and hours saved.
Most engagements start with a paid AI workflow diagnostic. It takes about two weeks and ends with a go/no-go decision on one workflow.
We take one bounded workflow from proof of concept to production, typically in six to eight weeks. We agree the acceptance criteria with you, then own the build, testing, launch and handover.
Best when you want one accountable team and a defined outcome. Most clients start here after the AI workflow diagnostic.
One senior engineer, or a small pod, joins your team under your leads and your sprint cadence. Use it as a dedicated AI squad on your roadmap, or as specialist staff augmentation for retrieval, LLM and multi-agent work.
This is collaborative delivery and capability transfer, not outsourcing.
Best when you have internal product leadership and need specialist AI engineers inside it.
We monitor usage, cost and quality, fix issues, and update models and prompts as providers change. When the first workflow is stable, we help you choose the next one.
Available after either engagement.
MegChem is a client deployment. ChatStack and Weaver are our own products, built and run in production by the same engineers, and they show the depth of our OpenAI build experience.

ADS built Meg AI, a voice-first knowledge agent, for MegChem. The pilot was live within two weeks and is being rolled out company-wide, with estimated efficiency savings in the hundreds of hours.
2 weeks
to a live pilot, now rolling out company-wide

Our own multi-agent platform turns a guided client conversation into clear requirements and a fixed-price estimate. It removed a bottleneck in our sales process.
2 months to 3 weeks
lead to conversion

Weaver brings Cursor, Jira, GitHub, Google Workspace, Figma and Slack into one view, so leaders see delivery progress, risk and AI usage without assembling updates by hand.
6 tools in one view
clearer delivery and adoption insight
The model is rarely the hard part. Adoption is. We treat the people and the process as part of the build.
We sit with the people who run the workflow before we design anything, on site in South Africa.
We connect AI to the systems your teams already use, rather than adding another tool to check.
Training, written guidance and early users who show colleagues why the solution helps.
The same engineers stay from diagnostic to support, so knowledge is not lost at each handover.
Yes. App Developer Studio is a South African team. Our Forward-Deployed Engineers work on site in Johannesburg, Pretoria, Cape Town and Durban, and remotely between visits.
We focus on engineering firms, mining suppliers and operations, and agriculture, where expert knowledge is scarce and documents are long. Typical first workflows are specification search, maintenance knowledge and service desks.
Your engineer uses company-approved accounts and only the access a task needs. We review data handling with your security, legal and POPIA teams before launch, and you keep control of your data, logs and intellectual property.
Book a free call. If there is a workflow worth examining, the next step is the paid AI workflow diagnostic, which takes about two weeks and ends with a go/no-go decision.
Yes. We deliver remotely, with planned site visits for discovery and launch.
A free call first. We will tell you whether a diagnostic is worth it.