I build AI and web applications—and help turn ambitious ideas into ventures that can ship.
I'm Gregory O'Connor, an MIT-trained product builder, strategist, and co-founder of Socure. Through Vociferous AI, I work from opportunity and market analysis through architecture, implementation, evaluation, branding, and launch.
Current work spans public-source intelligence, creative tools for actors and filmmakers, AI coaching, and a stealth AI-adjacent venture for fields where completeness, accountability, and accuracy matter most.
Available for select consulting engagements: application development, product strategy, technical diligence, and venture evaluation.
Selected work
Recent work across applications, venture building, and research. Public descriptions focus on what each project does and the capabilities involved; private methods and client information stay private.
- BNOW.NET — public-source intelligence application: a source-grounded application for analysts working with fast-moving public information. It is also a potential data source for future Epistemic analysis and a concrete defense-oriented example of the kinds of high-accountability systems that work may support. Read more →
- SceneFiend.app — scene and monologue discovery for actors: a built product opening in a small actor beta, with personalized recommendations, a curated public library, and a saved-book workflow for rehearsal and audition preparation. Read more →
- Dreamlet.Studio — a curated home for female-gaze cinema: a live, filmmaker-first platform pointing young cinephiles to short films that show women as fully realized people, now readying a focused marketing test. Read more →
- NaviaAI.com / Connection Coach — advisory and product work: advisory-board and product work supporting an AI executive-coaching company. Read more →
- Working Title: Epistemic — stealth AI-adjacent venture: developing systems intended to bring greater certainty to applications where completeness, accountability, and accuracy matter most. Potential vertical markets include pharmaceuticals, finance, law, and defense. The methodology remains private. Read more →
- Venture evaluation and advisory: business, brand, market, go-to-market, and financial analysis across fintech, infrastructure, legal and public-interest work, health, and emerging AI ventures.
I don't do political microtargeting, covert persuasion, or surveillance work. If your use case needs careful boundaries, we figure those out first.
Where this fits
I'm most useful when a founder or team has a real opportunity, partial information, and pressure to decide and ship. I can help determine whether the opportunity should become software, build a testable first version, and connect technical choices to market, cost, brand, and operating reality.
- AI and web application development, from scoped prototype through release candidate and handoff.
- Product and venture strategy, including technical diligence and build-versus-buy decisions.
- Market, brand, go-to-market, and financial analysis for early-stage ventures.
- Source-grounded knowledge and intelligence systems where accuracy, provenance, privacy, and human review matter.
- Evaluation and operating design: failure modes, costs, logging, governance, and what a team needs to run the system after launch.
How I work
Most projects start with one consequential problem, imperfect context, and too many plausible directions. I narrow the opportunity, connect the business case to a buildable product, and put something testable in front of real users. Quality, latency, cost, privacy, and failure modes become visible early; brand, market, and operating questions stay connected to the technical work rather than becoming a later handoff.
Prototype to release-candidate path
A useful first version is more than a demo that works on friendly inputs. I build the product path and the system together: scope, model behavior, retrieval, tests, deployment, and the handoff plan.
Product, market, and knowledge systems
Useful systems begin with the workflow and user, then connect positioning, source quality, model behavior, and what happens when the system is wrong. I keep those decisions in one loop so product and market problems surface before launch.
Architecture, evals, and what to log
Once a system has more than one model or service, the hard part is rarely the model. It is what calls what, what gets logged, what needs human review, and what becomes an audit problem later.
Working alongside your team
I can build independently or join an existing product or engineering team for the AI-specific work. The useful version is staying close enough to ship, then handing off the prompts, eval set, docs, and cost assumptions cleanly.
How engagements work
Start with the smallest engagement that can answer the important product or venture question.
Product + Architecture Sprint
1–2 weeksI examine the opportunity, users, workflow, data, market, and existing systems, then produce a build and validation plan with explicit go/no-go gates.
Prototype Sprint
2–4 weeksA working version in your environment, narrow enough to prove value. Includes evaluation, cost assumptions, and an honest read on whether to harden or stop.
Build + Ship
4–10+ weeksI stay with the build through integration, testing, and handoff. The goal is a system your team can operate without depending on hidden prompt tricks or heroics.
About
I'm Gregory O'Connor, an MIT-trained Ph.D., product builder, strategist, and co-founder of Socure, based in New York. I build applications and evaluate ventures at the point where technology, product judgment, and business reality have to agree.
My current portfolio includes BNOW.NET, SceneFiend.app, Dreamlet.Studio, advisory and product work with NaviaAI.com, and a stealth AI-adjacent venture under the working title Epistemic. Across that work, I also handle market, brand, go-to-market, and financial analysis—not only the software build.
I'm also a working actor with IMDb credits and a Shakespeare production scheduled for August 2026. That grounding in performance and film is part of why SceneFiend and Dreamlet come from inside the craft — how actors choose and prepare material, and which stories film chooses to center — rather than generic entertainment AI.
For stealth and client work, public descriptions stay at the level needed to establish capability. Private methodology, client information, and internal analysis remain private.
Send the workflow
A first email does not need to be polished. Tell me the opportunity, who it serves, what already exists, what data or systems are involved, and what would make a first engagement worth doing.