Wire production-grade LLMs into your existing systems. $100/hr or fixed-scope $5-30K. Not enterprise quotes, not POC theater · actual deployed code in your repo, observability wired in, cost controls baked in. Built by someone who actually ships LLM features in production. Direct line: 858-461-8054.
Each line is a concrete artifact you'll receive at the end of the engagement. No "AI strategy" without shipped code.
Provider matrix scored on latency, cost, accuracy, privacy. Fallback strategy across 2-3 providers. Cost model with per-request math.
Claude · OpenAI · Vertex · Bedrock · MistralPython / TypeScript / Go · matches your existing patterns. Reviewed for prompt-caching, streaming, error handling, retry logic, structured outputs.
Anthropic SDK · OpenAI SDK · Vercel AI SDK · LangChain (when warranted)Chunking strategy, embedding model selection, vector store, optional re-ranker, retrieval eval. Hybrid search if your data is mixed.
pgvector · Pinecone · Weaviate · Voyage · Cohere RerankSingle-agent or multi-agent. Custom tools wired to your APIs. Structured-output schemas. Loop detection. Cost guards.
Claude tool-use · OpenAI function-calling · Anthropic Computer Use (when warranted)Anthropic prompt caching wired up correctly (most teams miss this · 90% cost reduction on repeated context). Streaming for UX.
Anthropic cache_control · OpenAI prompt caching · streaming SSEEvery call traced with input/output, cost, latency, model, version. Filterable, searchable. p50/p95/p99 latency dashboards.
Langfuse · Helicone · Braintrust · OpenTelemetryRegression tests for prompts. Run on every prompt change. Golden-set examples curated with you. Pass/fail thresholds.
Braintrust · Promptfoo · pytest · Anthropic evalRate limits, max-token guards, model-routing rules (cheap model → expensive only when needed). Documented failure runbook + provider fallback procedure.
Token budgets · provider fallback · prompt versioningProvider choice is driven by your latency, cost, privacy, and accuracy requirements · not by what we have a partnership with.
Operator honesty: there are 5 situations where SideGuy is the wrong call. Naming them upfront so you don't waste a discovery call.
Posted prices because operator-honest means you should know the cost before the discovery call.
Ongoing LLM work, prompt-tuning sessions, eval-suite buildouts, cost-optimization audits. 15-min increments. Weekly invoicing.
Best when: scope is uncertain, you have an existing LLM feature that needs tuning, or you want a few hours of build help.
One LLM feature shipped to production · chat-with-your-docs RAG, doc summarizer, classifier endpoint, structured-extraction API. ~1-2 weeks.
Best when: one well-defined feature, you have a clean repo to deploy to.
RAG pipeline (chunking, embedding, vector store, re-ranker if needed) + production deploy + observability (Langfuse/Braintrust) + 1 agent workflow with tools. ~3-4 weeks.
Most common engagement. Best when: internal Q&A, support agent, sales-call workflow, doc analysis.
Multi-agent system + custom tool-use + hybrid RAG with re-rank + prompt-caching + fallback routing across 2-3 providers + full observability + eval suite. ~6-10 weeks.
Best when: multi-step research workflow, complex agent orchestration, high-volume production.
Comparison to typical alternatives: Enterprise AI consultancies start at $80K-$250K with quarterly executive readouts and POCs that often never reach production. AI agencies run $20K-$100K with enterprise-flavored quotes and 12-week minimums. SideGuy is structurally cheaper because there's no AE+SE+CSM trio, no SOW theater, and the work is done by the same person who scoped it.
Week-by-week reality of a typical Tier 2 engagement (RAG + production, $12K, ~4 weeks). Other tiers compress or expand from this baseline.
The 5 questions every prospect asks on the first call. Answered upfront so we can spend the call on your specific situation.
$100/hr hourly or $5K / $12K / $30K fixed-scope. Tier breakdown above. Compare to enterprise AI consultancies at $80K-$250K (often POC-only) or AI agencies at $20K-$100K with enterprise quotes. SideGuy is cheaper because there's no pyramid.
Claude (direct API + Bedrock + Vertex), OpenAI (gpt-4.1, gpt-4o, o3), Gemini/Vertex (2.5 Pro / Flash), Mistral, Llama via Bedrock/Together/Groq, Ollama for on-prem. Embedding: text-embedding-3-large, voyage, cohere, BGE-M3. Vector stores: pgvector, Pinecone, Weaviate, Qdrant, Turbopuffer. Provider choice is driven by your requirements.
Architecture doc + production-deployed code in your repo + version-controlled prompts + RAG pipeline + observability traces + cost controls + eval suite + runbook. Concrete artifacts. No POC-and-disappear.
Skip us if you need foundation-model training (call Anthropic / OpenAI), on-prem GPU procurement (call NVIDIA partners), $5M enterprise transformation (call Accenture/BCG X), or a SOC 2-certified AI platform (we integrate, we're not the platform).
Chat-with-your-docs RAG (legal-ops, 240 docs), sales-call summarizer + CRM auto-write (Series B SaaS), customer-support agent with 6 tools (DTC brand), compliance-evidence extraction from PDFs (fintech), internal Q&A bot (35-person agency), multi-agent research workflow (market-intel team). Prompt engineering, RAG, agents, tool-use, structured outputs, vision, production deployment.
Text PJ a paragraph about the LLM feature you want shipped. We'll reply within a few hours with a yes/no on fit, recommended provider, and a recommended tier · no discovery-call gauntlet, no email funnel.
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