The Trust Layer for AI

Like TCP guarantees reliable packet delivery regardless of network chaos, FORGE guarantees structurally valid output from any AI model — deterministic, zero-cost, and fail-closed.

17 Content Types
92 Repair Lanes
$0 Per Query
Live

AI is writing the world's code.
Nobody is checking the work.

AI output is now embedded in production systems across every industry. The defect rates, security failures, and trust erosion are all measured — and accelerating.

42%

of all committed code is now AI-assisted — projected to reach 65% by 2027.

1.7×

more issues per pull request in AI-generated code versus human-written code.

45%

of AI-generated code introduces OWASP Top 10 security vulnerabilities.

$2.41T

annual cost of poor software quality in the United States alone.

33%

of developers trust AI accuracy — while 46% actively distrust it, despite 84% using it daily.

$67.4B

in global business losses from AI hallucinations in 2024 alone.

Fixpoint Convergent Normalization

Every piece of AI output passes through a deterministic repair pipeline. No LLM calls. No probability. Pure structural transformation until the output converges to a fixpoint — or the pipeline fails closed.

Lane Separation

92 independent repair lanes, each specialized for a specific content-type and defect pattern. Lanes are isolated — a failure in one never affects another.

92 lanes × 17 content types

Bounded Iteration

The convergence loop repeats until the output is stable (input === output). Iteration count is bounded with a hard ceiling — no infinite loops, guaranteed termination.

while (output !== prev) { repair(); }

Fail-Closed

If normalization cannot converge within bounds, the pipeline rejects the output entirely. No partially-repaired content ever reaches downstream systems.

reject > propagate

Measured. Not Marketed.

Head-to-head benchmarks on identical defective inputs. Every number is reproducible from the test suite in the public repository.

System Parse Rate Defect Fix Security Fix Latency Cost / Query
FORGE 99% 100% 100% 36 ms $0.00
GPT-5.4 100% 96.9% 90.9% 4,831 ms $0.53
Claude 4.6 97% 89.8% 86.4% 21,203 ms $0.44
Gemini 96% 91.8% 72.7% 26,804 ms $0.12
134×
faster than GPT-5.4
590×
faster than Claude 4.6
744×
faster than Gemini

Gets Better With Every Deployment

When FORGE encounters a pattern it cannot repair, it doesn't fail silently. Anonymized failure telemetry feeds a continuous improvement loop — no human data leaves the pipeline.

Failure Telemetry

Anonymized structural patterns from failed repairs are collected — no content, no PII.

Clustering

Failure patterns are clustered to identify new defect classes and repair opportunities.

Algorithm Update

New repair rules are generated deterministically — no retraining, no stochastic tuning.

Validation Gate

Updates must pass the full benchmark suite before deployment. Regressions are impossible.

Ship

Validated updates deploy automatically. The system gets better with every cycle.

TCP for AI

In 1983, the internet faced a crisis of reliability. The Network Control Protocol assumed the network would be trustworthy — and when packets were lost, everything stopped. TCP solved this by moving reliability from the network to the endpoints: checksums, retransmission, guaranteed delivery. On January 1, 1983 — Flag Day — ARPANET cut over from NCP to TCP/IP, and the modern internet became possible.

Today, AI faces the same structural problem. Large language models produce probabilistic output with no native integrity guarantee. When that output is malformed — wrong schema, hallucinated structure, broken syntax — downstream systems halt, retry, or silently propagate errors. FORGE is the TCP layer for AI output. It guarantees that every piece of content leaving an AI system is structurally valid, cryptographically attested, and deterministically repaired — regardless of which model generated it.

The environmental stakes compound the urgency. U.S. data centers consumed 176 TWh of electricity in 2023 — 4.4% of all U.S. power — with AI inference accounting for the majority. Every malformed output that triggers a retry wastes energy, water, and compute. A single ChatGPT query consumes 6–10× the energy of a Google search. By eliminating the structural defects that cause retries at the source, FORGE doesn't just save money — it reduces the environmental cost of AI at scale.

Open Standard. Open Source.

Trust layers don't work behind closed doors. FORGE's normalization algorithms, benchmark suite, and ForgeStamp specification are fully open source — auditable by anyone, forkable by everyone, owned by no one.

View on GitHub MIT License Full Test Suite