Frontier
AI
Model teams need governed source data, synthetic evaluation sets, and simulation layers that reflect real business conditions.
Governed data infrastructure for consequential work
Move high-stakes data decisions from uncertainty to evidence.
Prelliquim helps teams source data they can defend, create working datasets they can test, and simulate outcomes before decisions reach the field.
Sigil — Compliant marketplace
Find the data you can actually use.
Sigil gives teams a disciplined way to source, assess, and access data with permissions, usage rights, and governance visible from the start.
Rights-aware discovery
Supplier and source context
Access paths built for review
Forge — Data creation
Create the working data your teams are missing.
Forge turns constrained, incomplete, or sensitive data problems into usable synthetic datasets for evaluation, modeling, and operational testing.
Synthetic dataset generation
Benchmark-ready test material
Safer experimentation loops
Cipher — Sector-driven simulation
Pressure-test decisions before they become commitments.
Cipher supports scenario design for sector-specific questions, helping teams compare paths, expose tradeoffs, and move with evidence.
Sector-calibrated scenarios
Decision pathway comparison
Outcome rehearsal before rollout
Operating arenas
Built for frontier systems and regulated work where evidence has to hold.
Prelliquim is designed for spaces where data quality, simulation, governance, and real-world consequence meet.
Frontier
Agentic systems
Autonomous workflows need testable data, decision rehearsal, and evidence boundaries before agents act in production environments.
Frontier
Robotics
Robotic systems depend on scenario coverage across perception, safety, operations, and edge cases that are hard to capture in the field.
Sustainability
Climate, resource, and infrastructure decisions need defensible data and simulations across regulation, demand, assets, and disruption.
Healthcare and life sciences
Data access, patient privacy, trial design, and model evaluation require evidence without casual exposure.
Financial services
Risk, compliance, fraud, and credit workflows depend on governed data and defensible scenario analysis.
Public sector
Policy, procurement, and service delivery need transparent sourcing and simulations that can withstand scrutiny.
Supply chain
Operational planning benefits from synthetic stress cases and sector context when real signals are incomplete.
Energy and infrastructure
Long-horizon planning demands scenario testing across assets, regulation, demand, and disruption.
Use cases
Use one product where the need is specific, or combine them when the workflow calls for continuity.
Data diligence
Evaluate whether a dataset is usable before procurement, ingestion, or model development begins.
Synthetic evaluation sets
Create controlled data for testing systems where production access is too slow, narrow, or sensitive.
Scenario rehearsal
Compare decision paths against sector conditions before operational, policy, or product rollout.
Governed AI readiness
Move from interesting data assets to evidence-ready workflows with fewer compliance dead ends.