Research Lab → Operator-grade System
Production-grade proof engines, verification pipelines, and live dashboards — engineered to push frontiers, not pixels. If a path exists, we’ll find it. If not, we’ll build the path and replay it deterministically.
Designed for labs, verifiers, and number-theory explorers.
Industrial verification, research automation, number-theory exploration.
Prove or falsify properties of mission-critical systems. SMT + FOL pipelines surface counterexamples with full traces and model witnesses.
Automate conjecture generation, lemma mining, dataset construction, and ablation study planning with entropy-aware search.
Live telemetry over symbolic runs: anomaly detection, decay maps, and operator consoles so researchers steer runs instead of babysitting them.
Orchestrated, observable, and built for frontier proofs.
The control plane. Multi-prover orchestration with deterministic pipelines for SMT + finite model testing, theorem synthesis, and entropy-guided scheduling. Every attempt emits structured traces for audit-grade replay.
A distributed numeric/symbolic explorer for chaotic regimes. Streams telemetry in real time, flags anomalies, and maps symbolic decay—so researchers can steer runs instead of babysitting them.
Analytic-number-theory engine for the critical line. Spectral methods for zeta/L-functions, zero-finding, spacing statistics, and prime-gap probes—wired into ProofX telemetry for reproducible experiments.
Live outputs from engines — interpretable, rigorous, and replayable.
Executive brief — positioning, applications, and philosophy.
ProofX unites formal theorem verification with symbolic AI experimentation. Its modular architecture blends GPU-accelerated numeric pipelines with custom first-order logic engines, orchestrated for deterministic, reproducible results.
Every proof attempt is transparent: visual proof-path tracers and symbolic heatmaps illuminate key steps, ensuring results are verifiable, reproducible, and scalable.
The primitives that make ProofX feel inevitable.
First-order logic with quantifier handling, skolemization, evaluation traces, and counterexample generation.
Deterministic pipelines for SMT + finite model checking, SAT bridges, and property proving.
Entropy-guided scheduling, decay maps, and anomaly detection across proof runs.
Operator-grade telemetry: streaming traces, evaluation walls, and drill-down for fast iteration.
ProofX stacks deterministic solvers with symbolic search and telemetry. Observability is first-class: every proof attempt is a data point.
Design target: truth-aligned latency — the fastest path from idea to verified evidence.
Architecture Deep DiveWe operate at the convergence of symbolic AI, number theory, and verification. Preprints, dashboards, and benchmarks are released on a rolling basis.
A research lab that scales like a systems company.
Ship public dashboards, replay seeds, and external proofs with full traces. Establish the ritual: propose → run → review → replay.
Expose curriculum schedulers, entropy knobs, and solver portfolios as programmable modes. Users author proof strategies, not scripts.
Compound engines into a copilot for conjectures, lemmas, and dataset creation. Research becomes an operational discipline.
We enter where verifiable results are mandatory: verification, fintech risk, safety standards, and frontier math. The stack generalizes across these, creating a shared OS for truth.
Compute and observability caught up with symbolic methods. Deterministic stacks + telemetry finally compress the iteration loop for verifiable work.
Systems, not slogans. Quiet rigor, public results.
Founder & Architect, ProofX
I build operator-grade symbolic systems. Trained on silence, tuned by constraints. I write code like a lab notebook—every decision logged, every result replayable. ProofX is a bet that truth deserves an operating system.
“If a path exists, we find it. If not, we wire the graph and try again—deterministically.”
Aggressive, testable, sequential.
Public dashboards, evaluation wall, and first external proofs with full traces.
Programmable orchestration modes; partner pilots in formal verification.
Private beta: research copilot for conjectures, lemmas, and dataset creation.
Investor & admissions quick-read.
Symbolic methods are compounding with modern infrastructure and data telemetry — enabling proof-at-scale and verifiable reasoning.
Deterministic solvers + entropy-aware scheduling + live dashboards — a tighter loop than generic LLM stacks for verification and research.
Evaluation walls, structured traces, and operator-grade UX — turning every run into reusable, compounding intelligence.
Yes. Private-cloud & on-prem via Docker. Deterministic seeds ensure reproducibility under restricted compute.
For academics and open dashboards, yes. Enterprise pilots are paid; private betas are case-by-case.
Send context (team, domain, timeline) to alkindi.proofx@gmail.com. We prioritize urgency + fit.
News and technical notes. RSS soon.
Public launch on Vercel with domain + SSL. Subdomains for docs/dashboards next.
We’re shipping quickly and selectively expanding pilot access.