A Apperdashery From AI to impact.

Use cases

Examples of AI agents we have built.

Recent examples of multi-agent systems we have designed and developed. Each one takes a slow, manual process and turns it into a fast, reviewable workflow, with a person kept in charge of the final call.

Use case 01 · AI agent app modernization

Modernize the software your business runs on, one safe step at a time.

The challenge

AI coding tools can generate code quickly, but your team still needs to understand the existing application, make the right changes, and verify that everything works as expected. Without a structured process for reviewing and testing AI-generated changes, speed gains can turn into additional rework and technical debt.

What we build

A team of AI agents, each with one job. They map what you have, plan the work in small steps, add tests that protect what works today, make the changes, and check each one independently.

The result

Steady, visible progress in small, tested changes your team approves, without a risky big-bang rewrite.

Leveraging AI agents to update software applications

Specialist agents do the work. Your team sets the direction and approves at key decision points.

You AI agents What you get Set the goal Approve the plan Try it and approve Scout Finds what needs changing List of changes Planner Breaks the work into steps Written plan Tester Records how things work now Safety checks Migrator Makes one step of the change A changed copy Reviewer Checks the finished step Written review Next step Needs fixes You AI agents Set the goal Approve the plan Try it and approve Scout Finds what needs changing You get: list of changes Planner Breaks the work into steps You get: written plan Tester Records how things work now You get: safety checks Migrator Makes one step of the change You get: a changed copy Reviewer Checks the finished step You get: written review Needs fixes Next step
Only the Migrator changes anything, and it works on a separate copy. It repeats with the Reviewer for each step, and nothing goes live until you agree.

Illustrative engagement.

Use case 02 · Safety & health regulations

Put the safety regulations in every worker's pocket, with the source on every answer.

The challenge

A construction crew on a job site needs to know what personal protective equipment is required for the work. The answer sits in federal regulations spread across hundreds of web pages, written in legal language and hard to search on a phone. A general-purpose chatbot might answer quickly, but nobody can tell where its answer came from.

What we built

A retrieval-augmented generation (RAG) system behind native iOS and Android apps. It indexes the OSHA regulations ahead of time, finds the sections that match a plain-language question, and provides answers with citations and links to those sections.

The result

A plain answer in seconds, tagged with the regulation number and linked to the original OSHA page, so anyone can check it.

Swift · SwiftUIKotlin · ComposeFastAPIChromaDBSentence Transformers
SourceIndexed ahead of time
OSHA regulation pagesConstruction · 29 CFR 1926PPE subpartsSection numbersSource URLs

Scraped, cleaned, split into sections and embedded. Each chunk keeps its citation and the link back to osha.gov.

Field questioniOS & Android app

When are safety nets required in construction?

Retrieval-augmented generation (RAG)API service
  1. ExpandTurns everyday wording like "do I need" into regulatory terms like "shall be provided".
  2. RetrieveFinds the five most relevant regulation sections in the vector store.
  3. GroundAnswers using only those sections, never from memory.
  4. CiteEvery requirement in the answer is tagged with its section number.

⚑ If the sections don't cover it, the answer says so

OutputAnswer + sources

Safety nets are required when the work surface is more than 25 feet above the ground or water and ladders, scaffolds, catch platforms, temporary floors, safety lines or safety belts are impractical (1926.105(a)).

1926.105(a) 1926.105 – Safety nets. osha.gov/laws-regs/regulations/standardnumber/1926/1926.105
Trust

Anyone can check the source

Each citation opens the original regulation, so the worker, the supervisor and the inspector are all reading the same text.

Demonstration project. Answers are informational and are not legal or compliance advice; always confirm requirements against the current regulation. OSHA is an agency of the U.S. Department of Labor. No endorsement or affiliation is implied.

Use case 03 · Investment research

Your AI investment research team

Five agents gather the data, find the outliers and explain them. You get a ranked, sourced brief and the final say on every trade.

What goes in

  • Watchlist & live quotes
  • Earnings & SEC filings
  • Analyst ratings
  • Market news from the web

Your AI agent team

  1. 1Quote scoutchecks every stock on your list
  2. 2Buy screenbig drops
  3. 2Sell screenbig jumps
  4. 3Rankerbiggest moves first
  5. 4News researcherfinds out why each moved

What you get

Daily opportunities brief

Ranked buys and sells, each with a reason, a verdict and a confidence level.

  • Company A −4.82%Supports buy
  • Company B −13.20%Mixed
  • Company C −27.31%Caution

Sample calls from real runs, Oct 2026

You review and approveEvery trade is previewed and placed only after you confirm.

Hours → minutes

A sourced brief, ready soon after the market opens.

Research changes the call

Agents flag when the news says “wait.”

Not investing? The same agent pattern works on your own numbers: sales reports, cash flow, vendor prices and competitor news. New to AI or already using it, we bring the technical expertise to build it.

Illustrative example. For informational purposes only. Not investment advice or a recommendation to buy or sell any security. Investing involves risk, including loss of principal. No endorsement or affiliation is implied.

Build with us

Have a process AI could help improve or take on?

We design and build multi-agent systems that do real work and keep your team in control. Tell us what is slowing you down.

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