Service

Formal Verification & Proof Automation

Formal methods and mathematical verification techniques ensuring AI system correctness, safety properties, and behavioral guarantees for critical applications.

Schedule Consultation Explore Research

Automotive

Autonomous Vehicles • Safety-Critical AI • Formal Verification

Uber's self-driving AI reclassified a pedestrian 6 times in 5.6 seconds — resetting her trajectory each time. It realized it needed to brake 1.3 seconds before impact. Physics said no. 🚗

$8.5M

Uber ATG settlement after fatal pedestrian crash caused by perception failure

NHTSA Investigation Report

40+

Active NHTSA investigations into Tesla FSD across 2.9M vehicles

NHTSA PE25-012

Interactive Technical

View details

From Stochastic Models to Deterministic Assurance

Autonomous vehicle AI systems reclassify objects mid-trajectory, resetting predictions each cycle. Without formal verification, probabilistic models create fatal blind spots in safety-critical decisions.

STOCHASTIC MODELS KILL SAFETY

Autonomous vehicles built on probabilistic AI suffer from classification oscillation, post-impact blindness, and sensor saturation. The gap between what AI perceives and what it should logically conclude has caused fatal incidents across Uber, Cruise, Tesla, and Waymo deployments.

DETERMINISTIC ASSURANCE ENGINEERING

Bird's-eye-view occupancy networks that track volume, not labels, eliminating classification oscillation
Formal verification with mathematical proofs ensuring safety-critical decisions meet deterministic thresholds
Sensor fusion combining LiDAR, radar, and vision with spatiotemporal consistency across occlusions
Assurance Gate architecture that transitions to minimal risk condition based on proof, not probability

Formal VerificationOccupancy NetworksSensor FusionBEVFormerPhysics-Constrained AI

Read Interactive Whitepaper →Read Technical Whitepaper →

Semiconductors

Semiconductor Design, EDA & Formal Verification

LLMs accelerate RTL generation, but hallucinations cause $10M+ silicon respins. 68% of designs need at least one respin (10,000× cost multiplier post-silicon). In hardware, syntax ≠ semantics, plausibility ≠ correctness. 🔬

$10M+

Cost of Single Silicon Respin at 5nm Node (mask sets + opportunity cost)

Veriprajna Neuro-Symbolic AI Platform 2024

68%

Designs Require at Least One Respin (industry survey data)

Industry Survey and Veriprajna Studies 2024

Interactive Technical

View details

The Silicon Singularity: Bridging Probabilistic AI and Deterministic Hardware Correctness

Veriprajna's Neuro-Symbolic AI prevents $10M+ silicon respins by fusing LLMs with formal verification, proving hardware correctness before tape-out using SMT solvers.

LLM HARDWARE HALLUCINATIONS

LLMs accelerate RTL generation but create race conditions causing $10M+ respins. Sequential training fails concurrent hardware semantics. 68% designs need respins.

NEURO-SYMBOLIC FORMAL VERIFICATION

LLMs generate RTL and formal assertions
SMT solvers prove correctness mathematically
Counter-examples guide automatic RTL refinement
Catches race conditions before tape-out

Neuro-Symbolic AIFormal VerificationSMT SolversSystemVerilog AssertionsZ3CVC5RTL GenerationVerilogSystemVerilogRISC-VAXI ProtocolBounded Model CheckingCounter-Example RefinementSilicon Respin Prevention

Read Interactive Whitepaper →Read Technical Whitepaper →

Financial Services

Enterprise Finance • Regulatory Compliance • Deep AI

Apple Card's broken code silently ate tens of thousands of consumer disputes. CFPB fine: $89 million. 💸

$89M

CFPB penalties and consumer redress against Apple and Goldman Sachs

CFPB Enforcement (Oct 2024)

$25M

liquidated damages Apple could claim per 90-day delay -- forcing premature go-live

CFPB Consent Order, Apple Inc.

Interactive Technical

View details

Engineering Absolute Compliance

A broken state machine in the Apple Wallet's dispute flow silently dropped valid billing disputes, exposing how multi-party fintech systems ship without formal verification of compliance workflows.

SILENT FAILURE AT SCALE

Apple's June 2020 update introduced a secondary form that broke the dispute pipeline. Tens of thousands of valid Billing Error Notices under TILA were silently dropped. Neither company investigated, and consumers were held liable for unauthorized charges they had already reported.

PROVABLY CORRECT COMPLIANCE

Model dispute workflows as distributed state machines using TLA+ and Imandra to flag dead states
Deploy multi-agent orchestration with Sentinel agents detecting stalled disputes autonomously
Verify API contracts between partners using SMT solvers for PCI DSS 4.0 compliance
Enforce regulatory timing via Performal symbolic latency guaranteeing 60-day resolution windows

Formal VerificationMulti-Agent SystemsNeurosymbolic AITLA+ / ImandraCompliance-by-Design

Read Interactive Whitepaper →Read Technical Whitepaper →

Build Your AI with Confidence.

Partner with a team that has deep experience in building the next generation of enterprise AI. Let us help you design, build, and deploy an AI strategy you can trust.

Connect via WhatsApp Email Our Team

Veriprajna Deep Tech Consultancy specializes in building safety-critical AI systems for healthcare, finance, and regulatory domains. Our architectures are validated against established protocols with comprehensive compliance documentation.