Initializing Interface...
Initializing Interface...
Vritanta deploys self-organizing AI swarms with System 2 deliberation, recursive meta-cognition, and Byzantine fault tolerance. No workers. Only outcomes.
Monte Carlo Tree Search with Chain-in-Tree optimization and automated Process Reward Models. Agents explore reasoning trajectories, backtrack from dead ends, and converge on optimal solutions.
MetaGen dynamically synthesizes agent roles and evolves communication topologies during inference. No static hierarchies. The network rewires itself around failures in real-time.
SDMA-PBFT consensus with confidence-probe weighted voting and cryptographic attestation. Every action is signed, verified, and anchored to an immutable proof-of-behavior ledger.
HyperAgent DGM-H modifies its own operational code. The system evaluates performance, diagnoses failures, proposes patches, and permanently integrates validated improvements.
Traditional vector databases treat memory as isolated embeddings. Vritanta models cognition as a dynamic graph where activation spreads along temporal, causal, and semantic pathways.
Biologically-inspired memory with spreading activation. Episodic nodes capture experiences. Semantic nodes abstract concepts. Fan Effect and Lateral Inhibition prevent hub explosion while enabling multi-hop retrieval.
Offline MCTS distillations are abstracted into reusable SGA atoms. During online execution, the agent retrieves relevant patterns and re-grounds them as soft reasoning hints — achieving System 2 depth at System 1 speed.
A special verification token inserted during generation enables token-level correctness estimation via LoRA-enhanced regression. Flawed reasoning paths terminate early, reducing decoding costs by 40%.
The enterprise ecosystem modeled as a high-fidelity digital twin. CMDB assets, identity graphs, network topology, and business impact parameters constrain all agent hypotheses to architecturally feasible actions.
No central orchestrator. Agents broadcast capabilities and needs into a semantic marketplace. The Semantic Router matches them via embedding similarity. Sub-teams form dynamically, dissolve after task completion, and solidify effective roles into reusable templates.
Hierarchical Practical Byzantine Fault Tolerance reduces communication complexity from O(n²) to O(n·k·log n). Localized consensus within regions, global consensus across masters.
Votes are weighted by internal model confidence, historical reputation, and adversarial probe detection. Severe conflicts trigger structured cognitive debates with judge adjudication.
Every memory write and agent action is verified against a Merkle root using SHA3-256 proofs. Finalized actions are recorded to an immutable proof-of-behavior ledger.
From first prototype to enterprise-scale swarm in 30 days. No seat licenses. No usage tiers. Only atomic outcomes.