- Multi-agent orchestration & autonomous tool use
- GraphRAG + hybrid retrieval & semantic reranking
- LLMOps / MLOps — model-to-production CI/CD
- Multimodal inference at edge & cloud
- Model Context Protocol (MCP) native, A2A-ready
- Reasoning-model gateway with test-time compute scaling
- Persistent agent memory + episodic recall
- AI governance, evals & explainability dashboards
- Post-quantum cryptography (PQC / CRYSTALS-Kyber)
- Confidential computing — TEE & secure enclaves
- AI-native zero-trust + SASE network mesh
- Prompt-injection & jailbreak defense at the gateway
- Continuous AI red-teaming + adversarial evals
- Ransomware resistance + SBOM supply-chain integrity
- Zero-knowledge proofs for private, compliant workflows
- Policy-as-code across cloud, edge & on-prem
- Platform engineering — GitOps, DORA metrics, chaos testing
- Serverless + Kubernetes, WASM edge runtimes
- Federated learning — data never leaves your perimeter
- FinOps & GreenOps — token, GPU & carbon visibility
- Inference routing, fallback & speculative decoding
- Zero Touch Provisioning — live in hours, not weeks
- SRE-grade observability: traces, metrics, logs, SLOs
A composable substrate for autonomous, tool-using agents — from prompt to production. MCP-native primitives, sub-agent delegation, and durable scratchpads let your fleet plan, act, reflect, and converge. Evaluator-optimizer loops, deterministic replay, and human-in-the-loop checkpoints turn experimental notebooks into auditable, mission-critical workflows. Bring your own model, retriever, or runtime — we orchestrate the rest.
- Reasoning-model routing across SOTA frontier LLMs
- Adaptive test-time compute & thinking budgets
- Mixture-of-Experts + speculative decoding
- Constitutional AI guardrails & refusal tuning
- Distillation pipelines: frontier → on-device SLM
- LoRA / QLoRA / DPO fine-tuning, one-click
- Model Context Protocol gateway — auth, audit, rate-limit
- 200+ pre-wired MCP servers (CRM, ERP, Git, BI, ITSM)
- Structured outputs + JSON-schema-grounded tool calls
- Computer-use & browser-control agents, sandboxed
- Function-calling marketplace with semver & SBOMs
- Dynamic capability discovery, A2A federation-ready
- Plan-act-reflect-converge orchestration patterns
- Sub-agent swarms with bounded blast radius
- Long-horizon memory: episodic, semantic, procedural
- Deterministic replay, prompt diffing & canary rollouts
- Continuous evals: regression, drift, hallucination
- Human-in-the-loop approvals + signed action receipts
Open lakehouse architecture — stream, store, query and govern in one control plane. Vector, graph, and time-series indexes are first-class citizens; embeddings, reranking, and hybrid retrieval are turnkey. Differential privacy and homomorphic encryption keep sensitive workloads compliant across jurisdictions. Synthetic data generation and model distillation accelerate fine-tuning without compromising provenance. Data mesh principles ensure domain autonomy without sacrificing enterprise-wide observability — and every byte is lineage-tracked, policy-governed, and AI-ready by default.
Already shipping: 10M-token context windows, agentic browser-use, MCP-federated tool meshes, continuous post-training, and on-device frontier-grade SLMs. In-flight: Agent2Agent swarms with cross-tenant trust attestation, world-model simulators for digital-twin planning, neuromorphic inference for sub-watt edge agents, and quantum-AI hybrid optimization for combinatorial workloads. Tomorrow's competitive moat is being deployed today — and it's all behind a single API key.
One vendor. Zero gaps. Infinite leverage. Built for the agentic decisions you're orchestrating today — and the post-quantum, frontier-scale threats you'll face tomorrow.
Talk to us about your AI strategy →