Bonus Health
Agentic IBT for Medicare
Built agentic IBT for Bonus Health to help improve the life expectancy of over 20 million Americans.
Agentic AI | Medicare | Healthcare
See selected work →CUSTOM SOFTWARE & AI AUTOMATION
We build custom applications, AI agents, and business automations that help your team spend less time on repetitive work. Our experienced engineers use AI-powered development tools to move from idea to useful software efficiently, starting with a defined scope and a fixed project price.
Start with one focused project. Build more when you're ready.

The Lokos approach
Automate document intake, data entry, reporting, handoffs, and other routine workflows so your team can focus on decisions and customers.
Begin with a useful first deliverable, put it in your team's hands, and improve it in focused iterations rather than waiting for one enormous launch.
Review the deliverables, price, and estimated timeline before work begins. When you need something new, request and approve the next scope separately.
From a single repetitive task to a full internal platform, we build software around how your business operates.
Replace manual intake, document handling, data reconciliation, approvals, and reporting with connected workflows.
Common problems: Manual intake, scattered documents and slow approvals.
An intake flow that collects documents, extracts information, and routes exceptions for review.
One intake workflow, agreed data fields and an exception review step.
Selected work
Examples of software and AI systems we've delivered. Each engagement starts with the problem, then the appropriate technology.
Bonus Health
Built agentic IBT for Bonus Health to help improve the life expectancy of over 20 million Americans.
Agentic AI | Medicare | Healthcare
See selected work →Infusense
Built a platform and machine learning algorithms for Infusense to analyze cannabis product composition and support safety in the industry.
Machine learning | Product analysis
See selected work →Flagships
Built systems for Flagships that use machine learning to analyze document engagement and connect private market signals to capital allocation outcomes.
Machine learning | Private markets
See selected work →How it works
Start with a single need. We turn it into a defined project, deliver the agreed work, and make it easy to keep improving.
Describe the workflow, bottleneck, or application you need. We'll help identify a practical first deliverable.
We prepare a statement of work covering what we'll deliver, the agreed fee, milestones, and acceptance criteria. You approve it before development starts.
Our engineers use modern AI development tools, review the work, and deliver against the agreed scope. You can track progress and request the next improvement through your client portal.
Start with a clear scope and a fixed project price.
Initial scopes are always fixed cost. For ongoing work, fixed-price projects and hourly engagements both work well; we agree the model that fits your needs. Each fixed-price quote covers an agreed scope, with new requirements and ongoing third-party costs identified separately.
Payment milestones and any upfront payment are specified in each statement of work.
Why Lokos
AI changes the economics of software development, but useful software still requires good judgment. We combine AI-assisted development with experienced engineers responsible for architecture, review, testing, and delivery. The result is a practical way to build what your business needs, one defined project at a time.
Questions, answered
Yes. Both fixed-price projects and hourly engagements work well. Initial scopes are always fixed cost, with agreed deliverables, a project fee, and acceptance criteria before work begins. For ongoing work, we agree whether a new fixed-price scope or hourly pricing best fits your needs. Existing hourly engagements remain available.
Yes. We often recommend a focused first deliverable, then expanding after your team has reviewed the result. We'll help define a sensible starting point.
We review what the software needs to do, its integrations, risks, and acceptance criteria. Then we propose a defined scope, price, and estimated timeline for your approval.
We document changes and provide an updated or additional scope and price before beginning work outside the original agreement.
No. We use AI-powered development tools to improve efficiency, while our engineers remain responsible for technical decisions, code review, testing, and delivery.
Often, yes. We can evaluate integrations with your current tools as part of scoping. Feasibility and any third-party costs are confirmed before they are included in a proposal.
Payment milestones and any upfront payment are specified in each statement of work. Clients can review agreements and manage payments through the portal.
Yes. You can submit additional requests as your needs evolve. For clients with regular development needs, we can also discuss a recurring development arrangement with clearly defined scope and capacity.
Lokos was founded by Diego Casabuena. He earned a bachelor's degree from NYU with majors in Computer Science and Economics. At NYU, he was a Phi Beta Kappa member and Presidential Honors Scholar. He completed his honors thesis, “Speaking of BERT,” under Rob Fergus and trained as a researcher at the NYU Center for Data Science during the first wave of modern language model work.
Before Lokos, Diego led machine learning at Podz, where his fine-tuned podcast transcription models became the world's first audio feed and helped lead to Podz's acquisition by Spotify. Over three years at Spotify, he progressed to Senior Machine Learning Engineer and shipped podcast previews, the audio-visual translation system that translated Lex Fridman and others, and contributed to Spotify DJ and Auto-Mix.
His work spans speaker diarization, language modeling, clustering, drone calibration, and large-scale ML engineering. Before Lokos, he also co-founded technology companies in the United States and Spain, giving him experience applying technical research inside early-stage businesses.
Recent thoughts from Diego and the Lokos team. Our observations.
We work with your team to define the requirements, build the software and deploy it into your existing systems.
Machine learning, software engineering and product experience in one team.
We work directly with the people who will use the software.
Research, data, models, product, and deployment.
Code review, automated tests and checks before release.
Start with a specific business problem.
Build a first version. Improve it with feedback.
Work directly with the engineering team.
Tell us where your team is losing time. We'll discuss a practical first project and outline the next step toward a scoped, priced proposal.
Email us your briefA short conversation to assess fit. No obligation to start a project.
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