How AI training transforms teams.
Real outcomes from marketing, sales, ops, product, and tech — built on role-specific workflows, not generic slides.
Why most ai fails.
You're paying humans to do things GPT-4 could do better.
Lead enrichment. Proposal drafting. Content briefs. SEO audits. Invoice processing. Every hour a senior operator spends on these tasks is an hour not spent on strategy.
Your automations are brittle Zapier chains.
One API change and three workflows break. No observability, no fallback logic, no retry strategy. You find out when a customer complains, not when the pipeline breaks.
You've tried AI tools. Nothing stuck.
ChatGPT Plus for the team. A Notion AI add-on. Maybe a brief Claude experiment. Point tools without an architecture — that's why nothing compounded. You need a system, not subscriptions.
Your data is siloed in six platforms.
CRM doesn't talk to the analytics stack. Support tickets don't inform sales intelligence. Marketing automation doesn't know what sales is doing. AI is only as good as the data it can reach.
Voice AI looks promising but you don't know where to start.
Inbound qualification. Outbound follow-up. Appointment setting. The use cases are obvious but the implementation isn't — and a bad voice agent destroys more trust than no agent at all.
You can't evaluate if AI is actually working.
No evals, no accuracy benchmarks, no ground truth datasets. You're running models you can't measure, in production, touching real customers. That's not automation — that's a liability.
Every tool in the arsenal.
Agent Orchestration
Multi-agent pipelines with LangGraph, CrewAI, or custom orchestrators. Directed acyclic graphs, retry logic, fallback agents, full observability.
- → LangGraph / CrewAI
- → Fallback + retry logic
- → LangSmith observability
RAG Pipelines
Retrieval-augmented generation on your docs, CRM, and knowledge base. Vector search, reranking, hallucination guardrails.
- → Chunking strategy
- → Vector DB (Pinecone/Weaviate)
- → Reranking + eval
Voice AI
Inbound and outbound voice agents built on ElevenLabs + Twilio. Real-time transcription, interrupt handling, natural conversation design.
- → Voice agent design
- → ElevenLabs + Twilio
- → Sentiment analysis
Lead Qualification
Automated scoring agents that enrich, score, and route inbound leads in under 60 seconds. Waterfall enrichment, ICP scoring, CRM writes.
- → Enrichment waterfall
- → ICP scoring model
- → CRM auto-routing
Content Generation
Brand-voice content pipelines producing SEO-ready articles, ads, and emails at scale. Human review gates, not blind automation.
- → Brand voice fine-tuning
- → SEO-aware generation
- → Review workflow
Workflow Automation
n8n, Make, and custom middleware connecting your CRM, ERP, support stack, and analytics. No more brittle Zapier chains.
- → n8n / Make pipelines
- → Webhook architecture
- → Error + retry handling
Proposal Generation
AI-assembled proposals from brief → scoped deck in under 2 hours. Pricing logic, scope templates, and brand voice — all automated.
- → Scope template engine
- → Pricing logic layer
- → PDF generation
Document Intelligence
Contract review, invoice extraction, RFP parsing — LLMs reading structured and unstructured documents with verified accuracy.
- → OCR + extraction
- → Confidence scoring
- → Human-in-loop gates
Customer Support AI
Tier-1 support agents on Intercom, Zendesk, or custom chat. Escalation logic, KB grounding, CSAT monitoring.
- → Support agent design
- → KB + RAG grounding
- → Escalation routing
Data Pipeline AI
AI-enriched ETL pipelines. Transform, classify, and enrich data as it moves — not after the fact.
- → Streaming transforms
- → LLM classification
- → dbt + BigQuery
Evals + Model Ops
Evaluation suites, accuracy baselines, A/B model testing, prompt versioning. You can't improve what you can't measure.
- → Eval dataset creation
- → Prompt versioning
- → Model A/B testing
Fine-tuning + RLHF
When base models aren't enough — fine-tuning on your data, RLHF pipelines, and domain-adapted models for specialized tasks.
- → Training data curation
- → Fine-tune pipeline
- → Inference optimization
How we work
Senior operators only. We embed in your tools, run the work, and leave a system you can run.
Workflow audit
We map every manual task in your growth stack — time spent, error rate, strategic cost. We rank automation candidates by ROI, not by what's trendy.
Agent architecture
Orchestrator topology, tool integrations, fallback logic, escalation paths, eval criteria — all designed before code is written.
Build + eval
Agents ship with evaluation suites and accuracy baselines. Nothing touches production without hitting thresholds on real-world data.
Observability + iteration
Every agent run logged. LangSmith traces reviewed weekly. Monthly model upgrades. Quarterly architecture reviews. The system compounds.