AI + PEOPLE COLLABORATION IN PROGRESS

ZERO OR IN-FLIGHT, TO DONE.
IDEAS TO PRODUCTION.

Syngen is a lean, synergistic blend of people and AI that carries a product or platform from strategy through data, AI, and engineering, so nothing gets lost in translation or a handoff. We can start from ideation or hit the ground running with what you already have, and we can bring our own team or blend into yours.

500M+users served by platforms we've built and run
3.5×revenue growth enabled through data & platform work
97%fewer inconsistent AI outputs, deterministic AI framework
90%less developer time spent on data instrumentation
30%cloud costs cut on the same infrastructure footprint
01The problem

SLIDES DON'T SHIP. TEAMS DO.

Most strategy work dies in the handoff. A deck goes to one team, a backlog goes to another, and six months later nobody remembers why. We close that gap by keeping strategy and build inside one team, with AI built into every layer, so the direction and the working system come out of the same room.

02Our approach

ONE TEAM. THE WHOLE STACK.

We live and breathe platforms, scale, optimization, and product experiences. No handoff between the people who decide the direction and the people who build it, same team, start to finish, and every capability below carries a number we can stand behind.

STRATEGY → PROTOTYPE

From the deck to the demo

We skip the slideware. Strategy turns into a working prototype in the same sprint, the same discipline behind leading Adobe's data and cloud transformation through a 3.5× revenue inflection, and founding four products before that, two of them acquired.

3.5×revenue growth led through platform transformation
4products founded, 2 acquired
16+years deep AWS cloud & streaming experience
25+years across startups to Fortune 500 delivery
ENGINEERING · PEOPLE + AI

Engineering without borders

Location-agnostic delivery, people and AI operating as one synergy, senior judgment paired with AI execution, not a human team with a chatbot bolted on. The same discipline that led a lean, cross-geo team serving a 30K-person product ecosystem.

30K+engineers, PMs, designers served by one platform
1,500+applications standardized on one architecture
20+reusable AI engineering skills in daily use
6msAPI latency held at 500M-user scale
DATA & INTELLIGENCE

Data platforms

Pipelines, lakes, and the intelligence layered on top, built for freshness and scale from day one. A standard data model and taxonomy that let 1,500+ apps and services build on one foundation instead of re-architecting for each new use case.

90PB+data lake, 300 trillion objects, 100TB+ ingested daily
140B+events processed daily, under 6ms latency
99%faster data recency, weeks to near-real-time
6 ninesuptime (99.9999%) sustained through live migrations
APPLIED AI & TRUST

Deterministic AI, disclosed by design

AI that behaves the same way twice, with provenance and disclosure built into the generation step, not bolted on after, the same governance model behind AI-content disclosure at consumer scale, years ahead of current AI regulation.

97%fewer inconsistent AI outputs
75%less manual intervention required
50%lower AI regeneration rate
~2Musers reached by AI-content provenance tagging
DEVELOPER PRODUCTIVITY

Time back to the people building

A common instrumentation standard and self-serve dashboards mean engineers spend their time building, not re-instrumenting the same event twice or hunting through logs to find out what broke.

90%less dev time on data instrumentation
2,000+automated dashboards self-serving ~10K engineers
95%faster mean time to detect (MTTD)
~100Kengineering hours saved per year
CLOUD & OPS EFFICIENCY

Cheaper to run, not just to build

Cloud spend treated as an architecture decision, not a finance afterthought. Right-sizing, consolidation, and vendor renegotiation applied continuously, not once a year.

30%cloud cost reduction on the same footprint
70%lower data collection costs after consolidation
40%savings from streaming billing optimization
1.5×cloud cost efficiency gained on one program
03The proof

OUR OWN AI, MEASURED IN THE OPEN

AI-IDS AI Instruction Design Set, a structured architecture for high-determinism, low-variance production AI

Most teams tune AI with adjectives and trial and error. We treat AI instructions like a software contract with defined roles, hard guardrails, and a documented order for resolving conflicts, published, model-agnostic, and used on every AI build we ship.

What we measuredBeforeAfter AI-IDS
Inconsistent AI outputbaseline−97%
Regeneration ratebaseline−50%
Manual intervention requiredbaseline−75%
Operational error rate, 25 rounds2.2%0%

Built and proven inside a production content platform generating 400K+ multimedia experiences across 80+ publishers, and now being formalized as a research submission establishing a repeatable framework for deterministic AI in enterprise production.

THE CATCH
Temperature and model choice alone don't close the consistency gap. Structure does. That's the whole thesis.
MODEL-AGNOSTIC
AI-IDS sits above decoding controls. It works on any model, because it's a spec, not a prompt trick.
ALWAYS SELF-SERVE
Every client gets the spec, the guardrails, and the eval results, not a black box they have to trust blind.
04What it looks like, built

RUNNING PLATFORMS, NOT SLIDES.

A sample of what's live, pulled straight from production, not a case-study template.

Platforms we've built

01
AI · Content Intelligence

AI-native content platform

Multi-model, multimodal pipelines turning stories into 400K+ multimedia experiences, including voice synthesis, contextual media, and programmatic scoring, across 80+ publishers and 15 channels, reaching 1B+ viewers, governed by our deterministic AI framework.

02
Data Platform

Enterprise data foundation

Consolidated 24+ systems and 330+ pipelines into one 90PB+ data lake processing 140B+ daily events, powering personalization, recommendations, and experimentation across 1.5K+ applications at 99.9999% availability.

03
Product · Growth

Product intelligence & growth platform

A standard data model adopted by 700+ applications, turning raw usage into product-led growth, recommendations, and operational intelligence, with a measured, multiple-times return on the business impact it drove.

How we build and govern

04
Engineering · People + AI

Engineers and agents, one delivery bar

Geo-distributed teams across the US, Europe, and Asia, working alongside AI agents as first-class contributors. This is an actual delivery model, not a headcount slide, governed by one written engineering standard regardless of timezone or whether the hands are human or AI.

05
Engineering OS

Human + AI engineering standard

An engineering operating system encoding years of architecture experience into 30+ specialized AI skills, the same synergy of people and AI we build for clients, running our own studio.

06
Trust & Governance

Compliant by design, at scale

GDPR, CCPA, and COPPA translated into system design, including data minimization, policy-driven access, and end-to-end lineage, across 50+ markets without slowing teams down.

05Who it's for

MADE FOR THE TEAM IN THE ROOM RIGHT NOW.

Whoever owns the problem, we plug in at their level. There is no separate track for "the business side" and "the technical side."

Marketing & Content

Ship more, from the same brief

Distribution-ready output across every channel from one brief and one brand profile, governed so nothing is fabricated and nothing repeats across channels.

Product & Growth

Turn usage into the next roadmap

A standard data model that made product-led growth, recommendations, and experimentation ship without every team rebuilding the same instrumentation.

Governance & Trust

Compliance that doesn't slow anyone down

Privacy, provenance, and audit trails designed into the system, not bolted on after legal asks. GDPR, CCPA, and COPPA are handled by architecture, at 50+ market scale.

The categories these teams are already buying, built natively, with AI infused from the ground up, not added as a chatbot on top:

Digital Asset Management Customer Data Platforms Marketing Automation AI Orchestration & Agent Harnesses Data Catalog & Lineage Video Platform Content Intelligence Product Analytics
06How we work

FOUR MOVES. NO CEREMONY.

Same four moves whether it's a two-week sprint or a year-long build.

01

Frame

Whiteboard the direction with your team. Output is a working prototype, not a 40-slide deck.

02

Design

Architecture and AI specs written as reviewable artifacts before a line of code exists.

03

Build

One accountable team, location-agnostic, people and AI in synergy, shipping weekly.

04

Measure

Every AI ships with a measured baseline. Every platform ships with visibility. No vibes.

07Where we've done this

INDUSTRIES WE'VE SERVED

Publishing & Knowledge Media & Content EdTech Marketing & Advertising Healthcare

We work with companies at

Early-stage & Venture Growth-stage Enterprise