AI Product DevelopmentWith Custom AI AgentsBuilt for Scale.
We engineer production-grade applications powered by the world's best language models — Claude, GPT-4o, Gemini, and more. Real streaming. Real tool use. Real reliability.
Launch your production-grade AI application.
We engineer intelligent systems with real-time streaming, robust tool calling, and deterministic JSON schemas.
Service 01
LLM App Development
We build production-grade applications powered by the world's best language models — Claude, GPT-4o, Gemini, and more. Real streaming. Real tool use. Real reliability.
Streaming Chat Interfaces
Real-time token streaming with Vercel AI SDK, Next.js Server Components, or Flutter streams. Zero perceived latency.
Tool Use & Function Calling
Claude tool use and OpenAI function calling — LLMs that search the web, run code, query databases, and call your APIs.
Structured Output & JSON Mode
Reliable JSON schema enforcement for downstream processing. No brittle parsing. No regex hacks.
Multi-turn Conversation Memory
Short-term conversation buffers, long-term memory with vector stores, and summary compression for infinite context.
Multi-model Routing
Smart routing: fast/cheap queries → Groq or GPT-4o mini. Complex reasoning → Claude 3.5 Sonnet. Cost optimized automatically.
Service 02
RAG Pipeline Development
Retrieval-Augmented Generation that connects your private data — documents, databases, APIs — to LLMs. Accurate, grounded, citation-aware answers at scale.
RAG Pipeline Architecture
Document Ingestion
PDF, DOCX, URLs, Notion, Confluence, S3 → chunked → embedded with text-embedding-3-large or Voyage AI
Vector Store Index
Pinecone or ChromaDB — hybrid search (dense + sparse BM25) for best recall. Metadata filtering for precision.
Query Rewriting + Retrieval
HyDE, multi-query expansion, re-ranking with Cohere. Top-K relevant chunks fetched in <100ms.
LLM Generation + Citations
Claude or GPT-4o answers with inline citations. Hallucination rate measured with eval suite on every deploy.
Multi-source Data Ingestion
PDFs, DOCX, URLs, Notion, Confluence, Google Drive, databases — ingested, chunked, and embedded automatically.
Hybrid Search (Dense + Sparse)
Combining vector similarity search with BM25 keyword search for dramatically better recall across all query types.
Query Rewriting & Re-ranking
HyDE, multi-query expansion, Cohere re-ranking — the RAG techniques that actually move the needle on accuracy.
Citation-Grounded Answers
Every LLM answer traces back to source documents. Users see exactly where each claim came from.
RAG Evals & Accuracy Tracking
RAGAS metrics: faithfulness, answer relevancy, context precision. Monitored per deployment with Langfuse.
Service 03
AI Agent & Workflow Automation
Multi-step autonomous agents that plan, reason, use tools, and execute complex workflows — without you having to babysit every step.
LangGraph Stateful Agents
Multi-node graphs with conditional edges, parallel branches, and persistent state. Agents that remember context across sessions.
Tool-Using Agents
Claude tool use, OpenAI function calling, and MCP servers — agents that search, code, execute, and call any API you connect.
Multi-Agent Systems
Orchestrator + specialist agent patterns: planner agents, researcher agents, critic agents — coordinated via LangGraph.
Human-in-the-Loop
Interrupt points for approval, correction, or escalation. Agents that know when to ask a human before taking irreversible actions.
MCP Server Integration
Model Context Protocol servers for standardized tool exposure — connect your internal APIs to any Claude-powered agent instantly.
Service 04
Flutter × AI Mobile Apps
Cross-platform mobile apps with embedded AI features — streaming LLM chat, on-device models, voice AI, and smart camera. One codebase for iOS, Android, and Web.
Flutter x Claude / GPT-4o Integration
Streaming LLM responses in Flutter with Dart async streams — real-time token rendering, tool use, and structured outputs.
On-Device AI with TFLite
Run lightweight models on-device: image classification, NLP, predictive input. Works offline, zero latency, full privacy.
Voice AI — STT + LLM + TTS
Full voice pipeline: Whisper speech-to-text → Claude processing → ElevenLabs TTS. Natural voice assistants in Flutter.
Vision AI & Camera Features
Google ML Kit, Vision API, or Claude vision — smart camera features that understand and describe what they see.
Firebase AI + Genkit
Firebase Genkit for serverless LLM functions, Firestore vector search, and tight Firebase auth/storage integration.
Service 05
Prompt Engineering & Evals
LLMs are only as reliable as their prompts. We design, test, and continuously improve system prompts with eval frameworks that catch regressions before users do.
System Prompt Architecture
Role definition, constraint injection, few-shot examples, chain-of-thought elicitation, output formatting — all engineered, not vibed.
Eval Suite Development
Golden dataset creation, scoring functions, and regression tests using Braintrust and PromptFoo. Runs in CI on every prompt change.
Red-Teaming & Adversarial Testing
We attempt to break your prompts before attackers do — prompt injection, jailbreaks, edge cases, and adversarial inputs.
Cost & Latency Optimization
Token budgeting, prompt compression, semantic caching (Helicone), and model routing to cut costs without hurting quality.
Observability with Langfuse
Full LLM tracing, cost-per-request tracking, user feedback loops, and A/B prompt testing in production.
Service 06
LLM Fine-Tuning
We fine-tune when it actually makes sense. Not as a first resort. When prompt engineering hits its ceiling, we train models that are faster, cheaper, and domain-perfect.
| Use Case | Prompt | Fine-tune |
|---|---|---|
| Custom tone/style | Works | Better |
| Domain vocab | Few-shot | Baked in |
| Fast iteration | Hours | Days |
| Low latency / cost | Full model | Smaller model |
| Complex reasoning | Claude wins | Risky |
| High-volume inference | Costly | Efficient |
Our Rule
We exhaust prompt engineering before recommending fine-tuning. If it needs fine-tuning, we tell you exactly why.
Dataset Curation & Preparation
We build high-quality training datasets from your existing content, user interactions, and expert annotations. Quality over quantity.
Open-Weight Model Fine-Tuning
Llama 3.1, Mistral 7B/Large, Qwen — fine-tuned with LoRA or QLoRA. Self-hostable, private, and cost-efficient at scale.
OpenAI Fine-Tuning API
GPT-4o mini fine-tuning for consistent formatting, tone, and domain knowledge — managed infrastructure, no GPU needed.
RLHF & DPO Alignment
Preference tuning with Direct Preference Optimization to align model outputs with human preferences and company values.
Post-Training Evals
Rigorous before/after benchmarks on your specific tasks. We ship fine-tuned models with eval reports proving the improvement.
Service 07
AI Strategy & Consulting
Not sure where to start with AI? We help you cut through the noise, audit your current stack, and build a practical AI roadmap that delivers business value — not demos.
AI Readiness Audit
We assess your data, infrastructure, team skills, and use cases. You get a clear picture of where AI will and won't work for you.
Build vs Buy vs Fine-tune Analysis
Honest advice: when to use APIs, when to self-host, when to build custom. No vendor bias. Just what makes sense for your scale.
AI Use Case Prioritization
We identify the 3 AI opportunities in your business with the highest ROI and lowest risk — and sequence them properly.
AI Risk & Compliance Review
Data privacy, model bias, hallucination risk, regulatory compliance (EU AI Act, GDPR) — assessed before you build.
Team AI Training
Hands-on workshops for your engineering team: prompt engineering, eval frameworks, LangChain, RAG architecture, vibe coding.
AI Consulting Engagement Flow
Free Discovery Call (30 min)
Tell us what you're trying to solve. We listen, ask hard questions, and give you honest initial thoughts.
AI Readiness Audit (1 week)
Deep dive into your data, stack, team, and use cases. Written report with findings and recommendations.
Roadmap & Architecture Design
Prioritized AI roadmap, technical architecture, model selection, and cost estimates. No fluff.
Build or Hand-off
We can build it with you, alongside your team, or hand off a fully documented spec for your engineers.
Use Cases
What Our Clients Actually Build
Real AI products across industries — not demos, not prototypes. Production systems.
Smart Crop Intelligence Platform
RAG pipeline over agronomic data + Claude vision API for crop disease detection. Reduced misdiagnosis by 70%.
Legal Document Analysis Agent
LangGraph agent that reviews contracts, extracts clauses, flags risks, and compares against standard templates.
Medical Knowledge Chatbot
RAG over clinical guidelines + eval suite ensuring zero hallucination. Claude with citation-grounded answers.
E-commerce AI Shopping Assistant
Flutter app with Claude-powered product recommendations, natural language search, and visual product matching.
Financial Report Summarizer
GPT-4o fine-tuned on financial terminology. Processes 200-page 10-Ks into structured executive summaries in seconds.
Personalized Learning Tutor
LangGraph agent with adaptive questioning, Socratic dialogue, and progress tracking. Flutter app, works offline via TFLite.
Construction Site Safety AI
On-device TFLite model in Flutter for real-time PPE detection. Flags violations and logs to Supabase instantly.
Customer Support AI Agent
Multi-agent system: triage → knowledge retrieval (RAG) → resolution or escalation. 80% ticket deflection rate.
AI Content Generation Studio
Fine-tuned Mistral for brand-consistent copy. Claude for long-form. Groq for real-time suggestions. All in one Flutter app.
Model Selection
We Pick the Right Model for Every Job
No religious wars. We use the best model for each task — and we route intelligently to balance cost, latency, and quality.
Anthropic Claude
claude-sonnet-4-5 · claude-opus-4
Complex reasoning, long documents, reliable tool use, coding, agentic workflows.
OpenAI GPT-4o
gpt-4o · gpt-4o-mini · o1
Multimodal tasks, structured JSON output, Assistants API, vision features.
Groq LPU
llama-3.1-70b · mixtral-8x7b
Real-time chat, autocomplete, high-throughput simple tasks. 800+ tok/s.
Meta Llama 3.1
llama-3.1-8b · 70b · 405b
Self-hosted deployments, fine-tuning, data privacy requirements, high-volume inference.
Mistral
mistral-large · mistral-7b
EU data residency, coding tasks, fine-tuning, GDPR-sensitive applications.
Google Gemini
gemini-1.5-pro · gemini-flash
1M token context, video/audio processing, Google Workspace integration.
How We Work
From Brief to Production in 5 Steps
A process built for AI products — iterative, eval-driven, and honest.
Discovery
Use case scoping, model selection, data audit, architecture planning. We tell you what will and won't work.
Architecture
System prompt design, RAG schema, agent graph design, vector DB setup, eval golden datasets.
Build
Full-stack development with continuous evals. Every LLM feature ships with a test suite.
Harden
Red-team testing, load testing, prompt injection defense, cost optimization, observability setup.
Launch & Iterate
Deploy with full monitoring. A/B prompt testing, model upgrades, and iteration based on real user data.
Results
Numbers That Matter
Reviews
What Our Clients Say About Us
Honest feedback from engineering directors, product managers, and founders building production AI.
“Initio delivered our Smart Crop Platform RAG pipeline in under 3 weeks. By combining Claude Vision with local agronomic data, they reduced disease misdiagnosis by 70%. Their evaluation rigor is unmatched.”
Dr. Elena Rostova
Director of AI, AgriSense Technologies
“The LangGraph agent Initio built for our contract review workflow is a game-changer. It analyzes 100-page agreements, flags risks, and extracts clauses with zero intervention. Highly recommend their technical depth.”
Marcus Vance
VP of Engineering, LexFlow Corp
“Our customer support agentic workflow deflected 80% of routine tickets in the first month. The multi-agent LangGraph system they designed handles complex billing and technical queries flawlessly.”
Sarah Jenkins
Head of Product, SupportSync Solutions
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AI Product?
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