Custom AI solutions, built for ourselves first.
AI agent development for the jobs a business repeats every week. Five systems, built for our own work first, each with its limits written in.
- 01Internal tool Publishing systemA day of slots, filled
- 02Live LeadsForYouA lead lands with its source
- 03Open source Cloud agentsHow far a credential reaches
- 04Internal tool AI-answer trackerFour assistants, one question
- 05Internal tool Outreach engineEvery claim checked before send
Each tile is drawn. Open one for the real thing.
What a custom AI solution is
Software built around one job a business repeats. AI agents do the reading, judging and writing; plain code does the parts that must never be wrong. Most of the work is around the model, and that is where a system earns trust.
Five Shorts and a long-form a day, from raw PS5 recordings.
Details
- In
- PS5 recordings from Nash Plays, a no-commentary gaming channel we run.
- Check
- A visual audit, then a click. Nothing publishes on its own.
- Series
- Numbered Shorts series, one playlist per recording.
Which buyers are ready now, and where is the proof?
Details
- Ask
- What you sell and to whom, where your buyers are, what makes one warm.
- Build
- Only from what buyers themselves published, each lead with its source link.
- Land
- On the seller's board, beside the marked samples.
An AI coding agent inherits your cloud credentials. What could it destroy?
Details
- Answers
- What those credentials could destroy, and whether the backups would survive.
- Access
- Read-only by default. A deterministic verifier checks every claim before the report.
- Writes
- Guardrail Terraform for a person to review. Never applied.
Where is the cloud spend nobody is watching?
- Reads
- AWS and GCP billing exports.
- Finds
- The spend nobody is watching.
- Access
- Read-only by default.
Both tools are published on MatrixGard's GitHub. KanavuLab is part of MatrixGard.
When a buyer asks an AI assistant who to hire, is your name in the answer?
Details
- Asks
- The questions buyers ask, every week, each in a fresh session.
- Logs
- Whether a brand is named, and which pages are cited.
- Flags
- A name that no cited page backs.
A first email is only as good as its facts. Every claim needs a source.
Details
- Reads
- Public signals: job posts, funding news.
- Validates
- Every claim against stored evidence. Anything unsourced blocks the email.
- Paces
- A warm-up cap on sending. A breaker pauses it when bounces rise.
The patterns these systems share
Five habits, read off the five machines. Where we start when we build one for you.
| Pattern | 01Publishing | 02LeadsForYou | 03Cloud agents | 04Answer tracker | 05Outreach |
|---|---|---|---|---|---|
| Evidence travels with the result | |||||
| A separate check comes first | |||||
| Read-only by default | |||||
| A person before anything public | |||||
| A record of what it did |
A mark means the habit is written into that system. Not every job needs every guard.
What we can build for you
Pipelines with an approval queue
From raw material to scheduled posts, with an audit before anything waits for your click.
Research agents that keep the source
Agents that read what is public about a company, a market or an AI answer, and keep the link for every fact.
Read-only audits and validators
Agents that inspect an account, a bill or a draft and report what they find, without changing it.
How a build works
- 01
Pick the job
A 20-minute call, then a written scope: the job, its inputs, and what done looks like.
- 02
Set the limits
What it may read, what it may never do, and the check before every result.
- 03
Build and show
Agents, tools, checks and the dashboard, shown working on real inputs.
- 04
Run and hand over
Where it runs and who looks after it, agreed before we build.
Who it is for, and who it is not for
A good fit
- A job your team repeats every week, with inputs a system can read: pages, files, exports or inboxes.
- You want a check and a record behind every result.
- You would rather start with one working system than a platform.
Not a fit
- Work that changes shape every time it is done.
- An agent with full access and no limits.
- A chatbot added to a site with no job to do.
Questions
What is a custom AI solution?
Software built around one job your business repeats. AI agents do the reading, judging or writing; plain code does what must never be wrong. Built for your data, your tools and your rules.
What is AI agent development?
Building software in which an AI model carries out a job with tools it is allowed to use: read a page, query data, draft a message. Most of the work is around the model: the tools, the limits, the checks and the record.
Can I see the systems on this page?
LeadsForYou is live at leadsforyou.in. Agent Radius and Ghost-hunter are open source on GitHub. The other three are internal tools: the tracker shows one real result, the rest are illustrations with sample data.
Do the agents act on their own?
Only inside limits agreed before the build: read-only by default, a person's click before publishing, or a validator that blocks anything unsourced. You choose which actions need a person.
Do you only build marketing tools?
No. These systems cover publishing, lead research, cloud security, AI answer tracking and outreach. If a job repeats and its inputs can be read, it is a candidate.
How much does a custom AI solution cost?
Scoped and quoted after a 20-minute call, once we know the job, its data and the checks it must pass.
Related
Tell us the job you repeat every week.
Scoped and quoted after a 20-minute call. If a simpler tool would do the job, we will say so on the call.