I build a lot of things.

Buyer / user

Robotics and embodied-AI engineers moving VLA policies from PyTorch research code onto Jetson, RTX, Apple Silicon, AMD, ROS 2, and production serving infrastructure.

The hard problem

A policy can export successfully and still be wrong, slow, incompatible with the device, or operationally unsafe. Existing tools fragment export, runtime selection, parity checks, rollout evidence, and rollback.

Core operating loop

1. 1Inspect hardware, Python, CUDA, TensorRT, providers, and model compatibility.
2. 2Export monolithic ONNX graphs and choose the best available runtime path.
3. 3Prove reference-vs-optimized parity with seeded inputs and numerical receipts.
4. 4Benchmark latency, promote a proof packet, and retain rollback/reproduction evidence.

Buyer / user

Robot-learning teams with LeRobot/TEL, egocentric, spatial, UMI, or multimodal demonstrations and a named policy, evaluator, task, and training budget.

The hard problem

Robot datasets often contain timing defects, missing evidence, leakage, rights constraints, inconsistent frames, and transformations whose downstream value is never measured.

Core operating loop

1. 1Ingest and checksum immutable raw bytes; preserve lineage and rights state.
2. 2Profile timing, media, missingness, conformance, uncertainty, and defect evidence.
3. 3Replay raw vs derived episodes and preview reversible treatments.
4. 4Compile a target-specific candidate and compare utility under a matched budget.
5. 5Approve, release, verify, recall, and recommend the next bounded data action.

Buyer / user

Creators, app teams, and marketers producing reaction videos, demos, ads, and short-form content that mix generated media with exact editorial control.

The hard problem

AI generation tools are fast but imprecise; traditional editors are precise but slow to explore. Moving assets between them creates export/re-import friction and breaks creative context.

Core operating loop

1. 1Build image, video, audio, and transformation chains on a visual node canvas.
2. 2Run edge-driven generation, inspect outputs inline, and star useful assets.
3. 3Switch the same asset store into a multitrack timeline without re-importing.
4. 4Trim, position, layer, synchronize, and export with native playback diagnostics.

Buyer / user

DTC brands with product-market fit and inventory but an underperforming TikTok Shop, affiliate, or short-form organic motion.

The hard problem

Brands produce disconnected content, recruit affiliates who go dormant, and make creator decisions from profiles instead of the videos and outcomes that actually demonstrate fit.

Core operating loop

1. 1Map live trends onto a brand-specific recipe, script, and five-beat shot sheet.
2. 2Render vertical creative from real product references behind human approval gates.
3. 3Log forecasts and ingest watch time, retention, sentiment, shares, saves, and GMV.
4. 4Learn per account; change one creative lever at a time and preserve the outcome trail.
5. 5In Framefound, research creators from video evidence, cluster patterns, shortlist, and compare.

Buyer / user

Consumers using guided visualization, affirmations, dream reflection, journaling, and intentional daily routines.

The hard problem

Most manifestation apps replay generic content, require a connection for the core loop, and treat personalization as a shallow prompt rather than a durable private context.

Core operating loop

1. 1Capture desires, context, narrator, tone, soundscape, duration, and reminders.
2. 2Generate title-first playlists; create a full present-tense story only when selected.
3. 3Play narrated sessions with karaoke highlighting, ambient mixing, and lock-screen controls.
4. 4Carry sessions into a searchable library, journal, vision board, and affirmation deck.

Buyer / user

Benefits leaders at self-insured employers, PBM consultants, and brokers managing contract terms, claims behavior, vendor responses, and renewals.

The hard problem

PBM contracts, claims, rebates, formularies, MAC lists, invoices, and renewal material arrive in different formats; potential leakage is difficult to trace back to the clause or record that supports it.

Core operating loop

1. 1Upload evidence and extract facts, sources, confidence, and missing inputs.
2. 2Map contract clauses to claims, spread, rebate, MAC, formulary, specialty, and NDC evidence.
3. 3Flag potential leakage and evidence gaps without overstating legal conclusions.
4. 4Draft data requests, challenge questions, follow-ups, response trackers, and renewal packets.

Buyer / user

Program owners, cohort managers, reviewers, and funded ecommerce members who need auditable operating decisions rather than scattered forms, chats, and spreadsheets.

The hard problem

Cohort operations combine intake, voting, store sequencing, late joins, attendance, learning, fulfillment, integrity, and member communication—each with different visibility and authority rules.

Core operating loop

1. 1Verify paid intake, assign a member to a group, and preserve assignment exceptions.
2. 2Collect structured submissions and adaptive reviews; deterministically score and freeze human results.
3. 3Run sealed Shadow AI, compare only after unsealing, inspect integrity, and stage learning reports.
4. 4Approve, publish, expose the right outcome to each role, and preserve source-linked receipts.

Buyer / user

People who want more control over how their speech is perceived across calls and meetings without replacing their voice or identity.

The hard problem

Accent conversion is a multi-objective systems problem: pronunciation must move, identity and words must survive, latency must stay interactive, and classifier movement must correspond to audible target progress.

Core operating loop

1. 1Capture normal speech and route transformed audio through a native virtual microphone.
2. 2Predict target phoneme/PPG-duration behavior while preserving source-speaker characteristics.
3. 3Evaluate identity, WER, accent movement, acoustic-reference progress, robustness, and latency.
4. 4Refuse a product claim when a metric improves but listening/acoustic evidence disagrees.

Buyer / user

Doctors, clinics, and patients handling prescriptions, credentials, patient records, documents, and follow-up across mobile devices.

The hard problem

Clinical information arrives through photos and documents, while identity, consent, organization boundaries, retention, and abnormal-result follow-through require much stronger controls than a generic consumer upload flow.

Core operating loop

1. 1Authenticate providers, create organization identity, and verify credentials.
2. 2Create patients and upload documents directly to signed storage locations.
3. 3Trigger asynchronous vision extraction and write structured prescription evidence.
4. 4Apply organization-aware access, rate limits, retention jobs, soft deletion, and PHI audit trails.