01
Find the bottleneck
What is actually costing you?
We look at where revenue, time, or capacity is being lost today.
I turn business bottlenecksinto working AI systems.
I build AI and software systems that help growing businesses capture more opportunities, remove expensive manual work, and get more output from the team they already have.
You bring me the bottleneck.
I figure out what should be automated, what should stay human, and build the system that fixes it.
Problem → system → production → measurable impact.
Built with teams behind products people actually use.
Where is your business losing time or money?
Usually, the problem isn't that you need more software.
It's that something important is still being done manually.
Maybe:
- Leads aren't being followed up consistently
- Your sales reps waste hours getting leads by hand
- Salespeople spend too much time researching instead of selling
- Information is stuck across different tools
- Your team repeats the same operational work every week
- You know AI could help, but don't know what should actually be automated
- The software you need simply doesn't exist
Bring me one expensive bottleneck.
I'll help you figure out:
- What's actually causing the problem
- What software or AI can solve
- What should stay human
- What I'd build
- Whether fixing it is actually worth the investment
If it is, I build the system end to end.
Book a 20-minute callWhat I do
I connect your tools, automate the busywork, and keep it running.
01
Revenue leaking through manual work
Capture more opportunities
If your sales or growth team is losing time finding information, qualifying leads, moving data between tools, or following up manually, I build the system underneath it.
More opportunities through the same team.
Look at this process →02Same work, every week
Increase your team's capacity
If people are spending hours repeatedly researching, reporting, copying information, checking systems, or handling predictable operational work, I turn the repeatable parts into software. People stay involved where judgment matters.
Less manual work. More output.
Look at this process →03Off-the-shelf doesn't fit
Build the software you actually need
Sometimes another SaaS subscription isn't the answer. You have a process specific to your business, and existing software can't handle it properly.
Your process, turned into software.
Look at this process →How it works
From “can we automate this?” to live and running.
You don't need to learn an AI stack or figure out which automation tool to use. That's my job.
02
Find the simplest fix
What should software solve?
I'll tell you what I'd automate, what AI can handle, what should stay human, and what doesn't need software at all.
03
Build the system
Make the whole thing work
AI, software, APIs, integrations, data, and the interface your team needs. Built end to end.
04
Put it into production
Measure whether it made the business better
The system gets used by real people. Then we look at the metric that mattered: more opportunities, more output, less manual work.
Production, not prototypes
I've built systems that run in the real world.
No toy demos. I've spent more than six years building systems used by real businesses, products, teams, and customers.
“Sam has been crushing it on an automated reply bot.”
15,000+
GitHub stars on the elizaOS runtime. Billing, credits, API keys, quotas, and usage infrastructure for thousands of hosted agents at Eliza Labs.
60%
Faster data-layer responses after five social APIs became one schema. Creators resolved across TikTok, YouTube, Twitter, Instagram, and Spotify. Shipped for Camp Network.
Problem → system → result
Case studies
01
Finding hundreds of qualified companies without doing the research manually.
Hiring signals, verified at the source, contacts attached, and ready for outreach. 351 live companies · 456 contacts.
Read case study →02Billing infrastructure for thousands of AI agents.
Usage tracking, credits, API keys, quota enforcement, and billing running in production. Thousands of hosted agents · plugin setup −70%.
Read case study →03Turning five messy data sources into one reliable system.
Multiple external platforms, one unified data model, built for a live product. Response times −60%.
Read case study →Where is your business losing revenue or capacity?
Maybe it's a lead that never gets followed up. Maybe your salespeople spend hours doing work software could handle. Maybe your operations team repeats the same process every single week. Maybe the tool you need doesn't exist.
Bring me the problem. I'll tell you what I'd build — and whether it's actually worth building.
Book a 20-minute callFrequently asked questions
What happens on the first call?
Tell me about one task or process that is costing your business time or money. We'll look at how it works today, what could be improved, and whether building something is worth it. You don't need a technical brief.
Do I need to know what to automate?
No. Bring the problem and show me how your team handles it today. I'll work out what software can do, where AI would help, and where a person should stay involved.
Can you work with the tools we already use?
I'll check your current tools first. Where they allow it, I connect them so information moves automatically. If something needs custom software, I'll explain why before we start.
How long does a build take, and what does it cost?
The scope sets the price and timeline. A focused first version can take around three weeks; larger builds take longer. We agree on what I'll build, the cost, and the timeline before work starts.
Will my team need to build or manage the system?
I handle the build and get it working with your team. People stay involved where a decision needs their judgment. We agree on handover and any ongoing support as part of the project.
Is Samarth Gugnani a blockchain developer?
No. Since 2023 his work has been data platforms, AI agent infrastructure, billing, and GTM systems. Early web3 work from 2020–2022 is dated experience.
Did Samarth found Eliza?
No. He was a senior software engineer and core maintainer at Eliza Labs who owned billing: credits, API keys, usage metering, and quota enforcement on Cloudflare Workers. The project's token peaked at a $2.5B market cap; that figure describes the project, not a company he owned.