// core capabilities / engine 03

Autonomous workflows. Production-grade execution.

We architect enterprise-scale AI agents, stateful RAG pipelines, and custom model coordination layers — transforming raw models into reliable operational infrastructure.

Initialize agentic review See how we ship

// agent.engine

Stateful AI workflows

Autonomous agents capable of multi-step reasoning, tool execution, and deterministic fallback routines. Move from passive insights to proactive execution — agents that run in production, not just demos.

// knowledge.vec

Advanced RAG architectures

High-fidelity retrieval — dynamic chunking, hybrid search, cross-encoder re-ranking. Secure data integration so synthesis stays context-aware and grounded, not hallucinated.

// tune.eval

Fine-tuning & evaluation

Adapt open-weights models to your proprietary data. Deterministic eval frameworks gate every change, so model outputs stay low-latency, cost-optimized, and accurate.

// agentic infrastructure control

Specialized squad. Embedded in your enterprise stack.

// production ai mandate included

Context-insulated data security & privacy compliance
Guardrail orchestration & hallucination triage layers
Model-agnostic routing (Anthropic, OpenAI, open-weights)
Real-time token, cost, and latency telemetry
Versioned eval suites — every prompt/model change gated

// engagement model active

The Autonomous Engine

Specialized engineering squad deploying deterministic AI systems directly into your enterprise stack. Embedded with your data/ops teams, shared code ownership, transparent eval scoreboards.

scope

Sprint-based · gated by evals

typical engagements: 8 – 20 weeks

Initialize agentic review

// how we ship

From data audit to live agents in production.

Every stage is gated by deterministic evals. We don't ship demos that drift — we ship pipelines with versioned guardrails and live telemetry.

For enterprises · ops teams · platform leaders

agent.vistriqo.com/pipeline

// agent deployment pipeline running

ingestion

Bottleneck & data audit

Evaluate operational bottlenecks, data dependencies, and target model benchmarks. Output: a scoped pipeline blueprint and an eval baseline.

embedding

Knowledge & retrieval layer

Engineer the data storage logic, knowledge graphs, and RAG vector pipelines. Chunking strategy + re-ranking + access controls.

agentics

Graph routing & tool access

Graph-based agent routing logic, custom memory constructs, and autonomous tool access. Guardrails + fallbacks baked into the architecture.

runtime

Production telemetry

Production deployment with continuous telemetry — cost, latency, drift, hallucination triage. Eval suites run on every model or prompt change.

$ agent.run("reconcile Q3 revenue")

→ plan: 3 steps identified

→ tool: crm.query · 412 rows

→ tool: ledger.match · 408 reconciled

→ eval: passed · drift 0.02

→ complete · awaiting review

// ready to deploy

Move from LLM wrappers to production agents.

Tell us the workflow you want to automate. We'll come back within two working days with an evaluation plan and a pipeline architecture you can ship against.

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