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Home/Services/Discipline 04
// Discipline 04

Agentic AI that works in production.

Multi-agent orchestration, tool-use, autonomous workflows. Not demos — production systems with measurable outcomes, built to be maintained.

// agentic_workflow · ReAct loop · streaming @ 42 tok/sACTIVELLM// thought_chain1. Analyze request context2. Decompose into subtasks3. Select tools: [search, code]4. Plan execution order →// tool_usesearch_web()✓run_code()✓read_file()✓write_doc()✓// streaming_output · 340 tokensBased on the market analysis, I've identified 3 keytrends: (1) increased demand in Q2, (2) supply chainoptimization opportunities, (3) pricing elasticity at12% threshold. Generated forecast model (R²=0.94) andexported results to analysis.csv with confidenceintervals. Ready for stakeholder review.340 tok · 8.1s · 42 tok/sReActthinkactobservecycle: 1 · latency: 8.1s · model: gpt-4
/ 4.1

Multi-Agent Orchestration

Coordinated agent networks with role separation, handoff protocols, and shared state management.

// agent_trace · planner → executor → verifier
PLANNER → task decomposed into 4 sub-tasks
subtask[1]: fetch_docs · subtask[2]: summarise
EXECUTOR → subtask[1] complete · subtask[2] complete
tool_calls: 3 · tokens_used: 2,841
VERIFIER → schema: pass · confidence: 0.92
state: shared ctx 4.2k tok · hops: 3 · latency: 1.8s

// Details

  • LangGraph, CrewAI, AutoGen frameworks
  • Planner / executor / verifier patterns
  • Shared context and tool registries
  • Human-in-the-loop checkpoints

// Output formats

PythonRESTAsync queues
/ 4.2

Generative Applications

Image generation, content pipelines, document generation — grounded in business logic and brand constraints.

// generation_pipeline · flux-dev · batch:16
model ............ black-forest/flux-dev
guidance ............ 7.5 steps: 28
resolution ............ 1024 × 1024
brand_lora ............ applied · weight: 0.7
moderation ............ pass · score: 0.02
throughput ............ 2.4 img/s · A100

// Details

  • Diffusion models (SDXL, Flux)
  • Document & report generation
  • Structured data synthesis for training
  • Content moderation pipeline integration

// Output formats

APIBatch pipelineWebhook
/ 4.3

AI Workflow Automation

Replacing multi-step manual processes with AI-driven pipelines that route, decide, and escalate correctly.

// workflow · doc_processing · invoice_v2
INGEST → PDF 14 pages → OCR → structured JSON
EXTRACT → vendor, amount, date, line_items (12)
ROUTE → conf: 0.94 → auto-approve
threshold: 0.90 · fallback: human_review
AUDIT → trace_id: doc_2847 · immutable log ✓
processed: 2,847 / 3,000 today · acc: 97.2%

// Details

  • Document processing & extraction
  • Decision routing with confidence thresholds
  • Escalation to human review
  • Audit trail and explainability

// Output formats

Pythonn8nZapier integration
/ 4.4

Safety & Guardrails

Output validation, content policy enforcement, and fallback chains. Production AI needs to fail gracefully.

// guardrail_trace · output_validation
schema_check ......... pass all fields present
content_policy ......... pass score: 0.01
pii_scan ......... clean no PII detected
halluc_check ......... WARN 1 ungrounded claim
action: fallback_chain triggered → retry ✓

// Details

  • Output schema validation
  • Content policy classifiers
  • Graceful degradation strategies
  • Monitoring and alerting

// Output formats

Policy configsAPILogs
// Work with us

Ready to ship? Let's scope it together.

Whether it's labeled data, a fine-tuned model, a RAG pipeline, or an agent running in production — bring us the brief. We'll scope it, price it, and tell you honestly if we're the right team. Inside 48 hours, no commitment.