Customer Briefing — Tier-1 Semiconductor
EVOLVINGLAB

Recursive
Self-Improvement
for Silicon Companies

We turn your proprietary IP, workflows and verification environment into an AI engineering system that gets measurably faster, better and cheaper every quarter.

Compounding velocity Sovereign moat Predictable compute
PROPRIETARY IP Golden RTL · specs WORKFLOWS EDA flows · scripts VERIFICATION Testbenches · sign-off RSI CORE PRODUCTIVITY Faster design & debug QUALITY Grounded in your IP COST Fixed compute budget KNOWLEDGE IN VELOCITY OUT EVERY TAPE-OUT MAKES THE NEXT ONE FASTER
Strategic Reality

Three reasons generic AI fails in silicon — and costs you your moat.

01 — Zero tolerance

Hallucinations are fatal

A software bug is patched in minutes. One clock glitch, CDC hazard or timing violation in silicon means a $50M+ respin and 9 lost months.

1 GLITCH · $50M RESPIN 9 MONTHS LOST
Looks like Verilog ≠ meets timing
02 — Sovereign moat

Commodity models erase your edge

Your edge is decades of golden RTL, specs and design decisions. Public models give everyone the same answer and leak IP. An AI that learns your workflows out-iterates everyone.

PUBLIC — SAME FOR ALL YOURS — COMPOUNDS ON YOUR IP
Internal IP → compounding velocity
03 — Cost trap

Runaway tokens, fragile results

Brute-force RAG with 100k+ token prompts burns the budget and still yields single-digit first-pass compile rates. No unit economics, no rollout to hundreds of engineers.

TOKENS PER TASK 100K+ FIRST-PASS COMPILE SINGLE-DIGIT %
Unpredictable spend stalls adoption
Customer Impact // Measurable Outcomes

Four outcomes your engineering leadership can measure.

01 — Velocity
40–65%
shorter iteration turnaround
TODAY 100% WITH EVOLVINGLAB 35–60%
  • RTL from specs, legacy blocks and guidelines
  • From “bug found” to “verified fix”, faster
02 — Grounding
>95%
alignment with internal guidelines
95% YOUR SPECS CODING STYLE ACRONYMS & LORE
  • Learns how your team designs
  • Beats generic models on proprietary blocks
03 — Economics
60–80%
lower token cost per task
LONG-CONTEXT RAG $$$$$ TASK-OPTIMIZED MODEL 20–40%
  • 5× more work on a fixed compute budget
  • Affordable for every engineering seat
04 — Control
Zero
IP leakage, zero AI-ops burden
YOUR FIREWALL PUBLIC
  • No AI platform team to hire
  • You own IP, access and eval thresholds
What We Deliver

Not an API key — an engineering system that improves itself.

01 — Scope

Discovery & scoping

Pick one high-value workflow. Set baselines, data permissions and task suites.

Milestones & acceptance
02 — Ingest

Knowledge integration

Authorized specs, legacy RTL, testbenches, bug history and coding conventions.

Domain intelligence
Core
03 — Execute

Model + agent loop

GENERATE RUN EDA DIAGNOSE REFINE
Self-correcting on real tools
04 — Measure

Evaluation & benchmarks

Pass rate vs. tokens, cost vs. success, and reproducible audit reports.

Objective verification
05 — Evolve

Deploy & evolve

Private on-prem or VPC, cost telemetry, and a model that improves as teams submit work.

Continuous compounding
EVERY SUBMITTED DESIGN MAKES THE NEXT RUN SMARTER
Where We Start // High-ROI Entry Points

Start with one bounded workflow a machine can grade.

SPEC → RTLVERIFICATION DEBUGSYNTHESIS & TIMING
Workflow A

Spec-to-RTL & subsystem design

InRegister specs, timing diagrams, FSMs
OutSynthesizable SV in your house style

AXI/PCIe bridges, DMA, peripheral controllers, arbiters.

First-pass syntax85%+ clean
Workflow B

UVM testbench & SVA assertions

InExisting RTL + interface protocol rules
OutCorner-case SVA, constrained-random sequences

Closes coverage blind spots and frees senior DV engineers.

Coverage closure+30%
Workflow C

Regression debug & root cause

InFailure logs, assertion triggers, VCD slices
OutRoot cause + a verifiable RTL patch

Days of waveform stepping become minutes.

Triage speed5× faster
Workflow D

Synthesis & timing closure

InSTA reports, setup/hold slack on critical paths
OutRestructuring advice: pipelining, fanout splits

Faster timing sign-off, less painful ECO churn.

Timing closure2× fewer ECOs
Proof of Value // Zero-Risk Validation

We prove it on a chip you already shipped — graded against your own answer key.

TAPED OUT 3–5 YRS AGO Completed project · Original specs · Regression testbenches · Known historical bugs · Timing-closure reports SENIOR ENGINEER'S FINAL SOLUTION INPUTSONLY RUNS BLIND EvolvingLab system never sees the answer SEALED Human answer key BLINDED A/B SCORE Compile / lint Root cause PPA / slack Cost / task ILLUSTRATIVE REPORT

Zero IP risk

Old projects carry near-zero commercial sensitivity. Legal and security can sign off fast.

Known ground truth

Specs, regressions, known bugs, timing reports and the senior engineer's final answer are all on file.

Zero contamination

Your RTL was never in public pre-training, so the result is an honest test of capability.

01
Compilation & lintPass rate vs. your baseline
02
Bug discoveryFinds the real historical root cause
03
PPA & timingSlack and area vs. senior designers
04
Unit economicsCost and hours per verified task
The Compounding Advantage

Every tape-out makes your next chip faster to build.

EACH GENERATION Gen N+1 builds faster than Gen N 01 — KNOWLEDGE IN Specs, errata, conventions 02 — THROUGHPUT Seniors 3× more productive 03 — FIRST-PASS Faster, safer tape-outs 04 — RE-TRAIN Telemetry refines the model
Engineering capability over timeIllustrative
GENERIC PUBLIC AI — STAYS LINEAR YOUR SOVEREIGN MODEL — COMPOUNDS TAPE-OUT 1TAPE-OUT 2TAPE-OUT 3N
Enterprise Governance // IP Safety

Three ways to deploy. Your crown jewels never leave your control.

Option A
Gold standard

Fully air-gapped, on-premises

YOUR DATACENTER MODEL INTERNET
  • Runs in your datacenter (DGX / H100 clusters)
  • No outbound internet; physical isolation
  • Weights, embeddings and telemetry stay inside
Defense & tier-1 fabless grade
Option B
Enterprise cloud

Dedicated private VPC

SINGLE-TENANT VPC MODEL YOUR KEYS PRIVATELINK YOUR EDA FARM
  • Single tenant in your AWS / Azure enclave
  • PrivateLink straight to your EDA compute farm
  • Customer-managed encryption keys
For hybrid-cloud compute teams
Option C
Ephemeral

Zero-data-retention enclave

TASK RAM ONLY WIPED ON EXIT RESULT NO PROMPT LOGS · NO TRAINING
  • Dedicated endpoints with ephemeral memory
  • Contract: zero prompt logging, zero training
  • Memory purged the moment a task ends
Fastest path to discovery & PoV
You keep full governance
Role-based access, immutable audit logs, and the right to revoke adapters at any time.
RBACAudit logSOC 2 / ISO 27001 aligned
Engagement Model // Low-Risk Adoption

Prove value in weeks. Scale only after the numbers are in.

PHASE 1 · PROOF OF VALUE · 4–8 WEEKS PHASE 2 · PRODUCTION ROLLOUT W1W2W3W4 W5W6W7W8 Scope & baselines Blinded sandbox run Executive ROI review GO / NO-GO ON HARD METRICS PERIPHERALS CPU NPU INTERCONNECT PHY NEXT TEAM MODEL KEEPS LEARNING

Phase 1 — Blinded value verification

Hard proof of speed and cost gains on one historical or sanitized dataset. You get a pass-rate vs. token-cost report and an ROI sign-off.

Phase 2 — Production scaling

Embedded in IDEs, GitLab/Perforce and CI regression grids. Expands from peripheral blocks to CPU, NPU, interconnect and PHY, learning from every design review.

Commercial Terms // Priced on Audited Value

One formula, three tiers. Every tier returns 6× its fee or more.

Growth tier

AI-chip startups & IP vendors

$400K – $600K / YEAR
Fits
Fewer than 75 DV engineers · at most one tape-out a year
Deployment
$250K one-time, foldable into the first-year fee
Includes
Agent runtime, private model with continuous updates, one shared forward-deployed engineer, fair-use agent runs
Worked example · your PoV scorecard replaces it
Base fee · < 75 DV band$400K
1 × 12nm program unit, 18-month program$200K / yr
Annual fee$600K
6–10×
RETURN ON FEE

Auditable value $3.6M–6.7M a year: freed DV capacity, avoided respin, schedule.
Priced so a seed-stage team can afford it before first silicon.

Division tier · where most customers start

One fabless business unit

$1.5M – $3M / YEAR
Fits
75–300 DV engineers · one or two tape-outs a year
Deployment
$1M – $1.5M one-time: EDA integration and in-situ fine-tuning on your IP vault
Includes
Agent runtime, private model with continuous updates, dedicated forward-deployed engineers, fair-use agent runs
Worked example · your PoV scorecard replaces it
Base fee · 75–300 DV band$1.5M
2 × 7nm program units$1.2M
Annual fee$2.7M
7–10×
RETURN ON FEE

Auditable value $20M–37M a year: freed DV capacity, avoided respins, schedule.
Booked against program NRE, so no seat count and no token meter.

Enterprise tier

Company-wide, three or more divisions

$6M – $10M / YEAR
Fits
Tier-1 fabless or automotive silicon · 600+ DV engineers across divisions
Deployment
$2M – $3M one-time: all EDA environments and IP vaults connected once
Includes
Everything in Division for every division, shared model that learns across the company, executive value reporting
Worked example · your PoV scorecard replaces it
3 × Division base fee$4.5M
6 × 7nm program units$3.6M
Volume discount, 10–15%−$0.8M to −$1.2M
Annual fee≈ $7M
8×+
RETURN ON FEE

Auditable value $59M–110M a year across three divisions.
One contract, one security review, one model that gets smarter with every division.

Annual fee = base fee by DV headcount band + program units × tape-outs a year. Program unit by node: ≥ 12nm $300K · 7/5nm $600K · ≤ 3nm $1M.

Proof first. Paid PoV $150–300K, credited 100% against deployment when you convert within 90 days. Three-year terms with design-partner price protection.

Your data, your adapters. Everything trained on your IP stays yours and runs inside the licensed runtime on your own GPUs. Zero egress, zero token meter.

Responsibilities // Zero-Burden Commitment

Four inputs from you. Everything else is on us.

What we need from you
One concrete use casee.g. a controller RTL block or a UVM coverage gap
One historical datasetA project from 3–5 years ago with known results
Verifiable success criteriaLint/compile commands, regression scripts, timing targets
Two points of contactOne senior DV/RTL lead and one engineering director
What you don't need to do
Hire an in-house AI model, training or inference team
Build or maintain agent frameworks and prompt chains
Guess which foundation model fits which silicon task
Expose your whole codebase or commit compute capital before value is proven
Engineering Creed // Honesty & Rigor

Zero hype. Physics decides.

What others promiseWhat we actually say
“We'll compress a 2-year chip cycle into 2 weeks.”
We speed up the high-frequency loops — verification, debug, ECO — to multiply team throughput.
“100% accuracy, zero hallucinations.”
LLMs are probabilistic. Our verification loops catch hallucinations before an engineer ever sees them.
“AI will replace your architects and DV engineers.”
We take boilerplate and log parsing off senior plates so they focus on microarchitecture and PPA.
“Dump in your raw data and the model gets smart.”
Domain intelligence takes careful curation, schema alignment and task-specific benchmarks.
“Here's an API key — deployment is your problem.”
We deliver a working engineering system, continuously optimized, with verified outcomes.
Next Steps

Start with a 30-minute technical discovery.

No upfront budget. Real historical silicon. Hard numbers.

Step 01
30 min

Technical discovery

Meet our silicon and verification architects. Find your biggest bottleneck and candidate tasks.

Step 02
1 block

Pick one historical IP block

A completed 3–5 year-old block with its specs, regression suites and bug errata.

Step 03
4–8 weeks

Run the blinded PoV

Inside your secure enclave. You get pass rate, token cost and ROI — measured, not promised.

Get in touch
EvolvingLab silicon engineering team
contact@evolvinglab.ai  ·  evolvinglab.ai
Schedule a discovery call
EVOLVINGLAB Cover
Confidential — Customer briefing 01 / 12
← → navigate · O overview · N notes · T pricing tier · F fullscreen
Contents
EvolvingLab — Customer Briefing