# dyta.ai — Full AI Knowledge Base & Context Specifications
=========
URL: https://dyta.ai
Tagline: Built AI-native. From the ground up.
Description: dyta.ai builds custom AI software, automation agents, and intelligent integrations for businesses ready to lead with AI — with 100% IP ownership.

## 1. Value Proposition & Positioning
What makes us different from every other "AI agency."
We're not a generic digital agency that added "AI" to the pitch deck. Every service, every build, every team member is oriented around AI-native delivery.

### D.01 AI-native by default
Every product we build ships with AI features baked in — RAG search, intelligent agents, smart automation. AI isn't an add-on, it's the architecture.

### D.02 Model-agnostic
We're not locked to a single vendor. OpenAI, Claude, Gemini, open-source — we pick what works best for your use case and budget, then make it swappable.

### D.03 Strategy to production
From feasibility assessment to deployed system, we handle the full lifecycle. No handoff gaps between 'the strategy people' and 'the build people.'

### D.04 You own everything
All code, models, prompts, and documentation transfer to you. No vendor lock-in, no proprietary platforms, no ongoing dependency on us unless you want it.

## 2. Engineering & Delivery Process
A clear path from problem to production.
Every engagement follows the same disciplined process. No black boxes — each stage produces a concrete, tangible deliverable.

### Step 01: Discover
Details: Understand your problem, data, constraints, and goals. Map the opportunity landscape.
Deliverable: Opportunity Map + AI-Readiness Score

### Step 02: Design
Details: Architecture, AI strategy, and solution blueprint. Clear specs before any code is written.
Deliverable: Technical Spec + Prototype Scope

### Step 03: Build
Details: AI-native development with continuous demos, evaluation, and feedback loops.
Deliverable: Production Code + Eval Suite

### Step 04: Launch
Details: Production deployment, documentation, team handoff — and optional ongoing support.
Deliverable: Deployed System + 100% IP Handoff

## 3. Technology Stack & Merits
Model-agnostic by design, production-grade by default.
We are not tied to a single vendor. Every layer is chosen on merit and matched to your specific requirements — then wrapped in testing so nothing ships blind.

### AI Models & LLMs (models/*)
Technologies: GPT-4o / GPT-4.1, Claude (Anthropic), Gemini (Google), DeepSeek, Llama / Mistral, Fine-tuned models

### Frameworks & Tooling (runtime/*)
Technologies: LangChain / LangGraph, Vercel AI SDK, MCP Protocol, LlamaIndex, Semantic Kernel, pgvector

### Application Stack (app/*)
Technologies: ASP.NET Core, Next.js / React, Astro, Node.js, Postgres, Redis

### Delivery & Ops (deploy/*)
Technologies: Azure / AWS, Docker, GitHub Actions, Vercel, Monitoring, CI/CD pipelines

## 4. Trust, IP Ownership & Evaluation
AI done right means AI you can trust.
We build AI systems the way serious engineering should work — measurable, documented, and fully yours when the project ends.
Key Commitments: Full IP Transfer | Source Code Handoff | Documented Architecture | Evaluation Suites

- You own everything: All source code, model artifacts, prompts, and documentation transfer to your organization. No lock-in, no proprietary dependencies.
- Evaluation & guardrails: Every AI system ships with evaluation suites, PII filters, and quality checks. We measure performance with real data, not vibes.
- Transparent process: No black boxes. You see the architecture, the evaluation results, and the decision rationale at every stage. Full documentation on handoff.

## 5. Engagement Models
### AI Strategy Assessment (1-2 weeks) 
Best For: Best when you know AI could help but aren't sure where to start.
Includes:
  - Opportunity mapping
  - Build-vs-buy analysis
  - Prioritized roadmap
  - Cost estimates

### Focused Build (4-12 weeks) [MOST COMMON]
Best For: Best for shipping a specific AI feature or product into production.
Includes:
  - Dedicated senior team
  - Production-ready system
  - Testing & evaluation
  - Documentation & handoff

### AI-Native Product Build (8-16 weeks) 
Best For: Best for building a new product or platform with AI at the core.
Includes:
  - Full-stack development
  - AI architecture design
  - Iterative delivery
  - Team capability transfer

### Ongoing Partnership (Monthly) 
Best For: Best when you need continuous AI development and support.
Includes:
  - Dedicated capacity
  - Multi-project delivery
  - Priority support
  - Regular strategy reviews

### Fit Check
Good Fit:
  [YES] You know AI could improve your product or operations, but you need the right team to build it.
  [YES] You want production-quality software, not a demo that impresses in a meeting and breaks in the real world.
  [YES] You value transparency — you want to see the architecture, understand the trade-offs, and own the result.
  [YES] Your team wants a partner who documents and hands off, not a vendor who creates dependency.
Not a Fit:
  [NO] You're looking for the cheapest possible prototype to test a vague idea.
  [NO] You need a generic website with no real AI functionality.
  [NO] You expect AI to magically solve problems without clear data or requirements.
  [NO] You want it live next week regardless of quality.

## 6. Pricing Tiers
### Foundation Tier
Starting Price: $2,500 (per engagement)
Tagline: Quick wins, clear value
Description: Fast-turnaround AI solutions for teams getting started. Lightweight chatbots, LLM integrations, strategy assessments, and training — delivered in days to weeks.
Features Included:
  - Lightweight AI Chatbot Deployment
  - LLM API Integration Consulting
  - AI Content/SEO Tooling
  - AI Strategy / Opportunity Assessment
  - AI Process Audits
  - AI Training/Enablement
  - AI-Powered Dashboards/BI

### Core Tier
Starting Price: $10,000 (per project)
Tagline: Production AI, personally led
Description: Our main delivery tier. RAG knowledge systems, AI agent automation, integration retrofits, and full AI-native software builds — led by senior engineers from start to finish.
Features Included:
  - RAG-Powered Knowledge Assistants
  - AI Agent Automation
  - AI Automation (workflow)
  - Document/Data Processing AI
  - AI Integration Retrofits
  - AI Middleware / API Orchestration
  - AI-Native Custom Software Builds
  - Natural-Language-to-SQL

### Frontier Tier
Starting Price: $25,000 (per engagement)
Tagline: Premium, cutting-edge capabilities
Description: Advanced AI capabilities at the leading edge. Custom MCP servers, voice agents, fine-tuned models, and predictive analytics — built in partnership with top AI platforms.
Features Included:
  - Custom MCP Server Development
  - AI Voice Agents
  - Fine-Tuned/Custom ML Models
  - Predictive Analytics / Forecasting

## 7. Full Service Catalog (19 Services Across 6 Categories)

=== Category: Data & Insights (data-insights) ===
Target Buyer Intent: We need to talk to our own data
Category Description: AI systems that make your business data queryable, understandable, and actionable — from knowledge assistants to predictive analytics.

#### Service: RAG-Powered Knowledge Assistants (rag-knowledge-assistants)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Chat with your data — grounded, cited, trusted
Summary: Internal knowledge bases and support bots trained on your own content. Every answer is grounded in source material with full citation traceability.
Full Description: We build retrieval-augmented generation systems that turn your fragmented documents, wikis, and records into a single queryable source of truth. Whether it's customer support deflection, internal knowledge lookup, or research acceleration — every response is grounded in your actual data, not hallucinated from training.
Capabilities: Custom knowledge base ingestion from docs, PDFs, wikis, and databases; Hybrid search with semantic + keyword retrieval; Citation-backed answers with source document linking; Incremental content updates without full re-indexing; Role-based access control on knowledge sources; Multi-format output — chat widget, API, Slack/Teams integration
Deliverables: Deployed RAG assistant (chat UI or API); Content ingestion pipeline; Admin dashboard for content management; Integration with your existing tools
Tech Stack: OpenAI, pgvector, LangChain, Postgres, Redis

#### Service: Natural-Language-to-SQL (natural-language-to-sql)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Let non-technical staff query data in plain English
Summary: A governed text-to-SQL layer that lets business users query production databases in natural language, safely and accurately.
Full Description: We build a semantic interface between your team and your database. Non-technical users ask questions in plain English and get accurate, validated SQL results — with guardrails to prevent unsafe queries, cost overruns, or data leaks.
Capabilities: Schema-aware natural language query synthesis; Query validation and cost guards; Row and column level access enforcement; Explainable query plans in plain English; Continuous accuracy improvement from user feedback
Deliverables: Natural language query interface; Semantic layer configuration; Access control and audit logging; User onboarding guide
Tech Stack: OpenAI, Postgres, dbt, Python

#### Service: AI-Powered Internal Dashboards/BI (ai-dashboards-bi)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: AI-generated insights on top of your existing data
Summary: Business intelligence dashboards enhanced with AI-generated insights, anomaly detection, and natural language summaries of your key metrics.
Full Description: We layer AI capabilities onto your existing business data to surface insights that traditional BI tools miss. Automated anomaly detection, trend summarization, and natural language reporting — so your team spends less time building dashboards and more time acting on insights.
Capabilities: AI-powered anomaly detection and alerting; Natural language metric summaries; Automated trend analysis and forecasting; Integration with existing data warehouses; Custom dashboard design and deployment
Deliverables: AI-enhanced dashboard application; Automated insight generation; Alerting and notification system; Team training documentation
Tech Stack: Python, OpenAI, Postgres, React

#### Service: Predictive Analytics / Forecasting (predictive-analytics)
Status: LAUNCH | Tier: FRONTIER | Delivery: in-house-partner
Tagline: Demand forecasting, churn prediction, price optimization
Summary: Machine learning models for demand forecasting, churn prediction, price optimization, and predictive maintenance — trained on your historical data.
Full Description: We build custom predictive models that turn your historical data into actionable forecasts. From demand planning to customer churn prediction, each model is trained on your specific data patterns and integrated into your decision-making workflows.
Capabilities: Custom ML model training on your data; Demand forecasting and inventory optimization; Customer churn prediction and retention modeling; Price optimization and elasticity analysis; Predictive maintenance scheduling
Deliverables: Trained predictive model(s); Integration API / dashboard; Model performance monitoring; Retraining pipeline documentation
Tech Stack: Python, scikit-learn, TensorFlow, Postgres


=== Category: Automation & Agents (automation) ===
Target Buyer Intent: We're drowning in manual work
Category Description: AI agents and automation that handle repetitive tasks, process documents, and execute multi-step workflows — so your team focuses on what matters.

#### Service: AI Agent Automation (ai-agent-automation)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Agents that take real actions across your systems
Summary: Multi-step workflow agents that handle data entry, reports, triage, email, and more — executing real actions across your tools with human-in-the-loop checkpoints.
Full Description: We build AI agents that go beyond chat — they execute multi-step workflows across your internal tools. From processing incoming requests to generating reports and routing tickets, these agents take real actions while keeping humans in the loop for high-stakes decisions.
Capabilities: Multi-step task execution across internal tools and APIs; Human-in-the-loop approval gates for critical actions; Durable execution with state recovery on failure; Integration with email, Slack, CRMs, and internal systems; Full audit trail of agent reasoning and actions; Custom tool and function definitions per workflow
Deliverables: Deployed AI agent workflows; Admin dashboard for monitoring and approvals; Integration connectors for your tools; Runbook and escalation documentation
Tech Stack: LangGraph, OpenAI, TypeScript, Postgres, Redis

#### Service: AI Automation (ai-workflow-automation)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Reduce manual work across your operations
Summary: Umbrella workflow automation that identifies and eliminates repetitive manual tasks across your operations using AI-powered decision making.
Full Description: We analyze your operational workflows to find high-impact automation opportunities, then build AI-powered solutions that reduce manual load. Unlike simple RPA, our automations understand context and make intelligent routing decisions.
Capabilities: Process discovery and automation opportunity mapping; AI-powered decision routing and classification; Integration with existing business tools; Exception handling and human escalation; Performance tracking and ROI measurement
Deliverables: Automated workflow system; Integration with existing tools; Monitoring and reporting dashboard; Operator training documentation
Tech Stack: Python, OpenAI, n8n, Postgres

#### Service: Document/Data Processing AI (document-data-processing)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Invoice extraction, contract analysis, form parsing
Summary: AI-powered document processing for invoices, contracts, forms, and unstructured data — extracting structured information at scale with LLMs and OCR.
Full Description: We build document processing pipelines that combine OCR, LLMs, and structured extraction to turn your paper-heavy workflows into automated data pipelines. From invoice processing to contract analysis, each solution is tuned for your document types and business rules.
Capabilities: Multi-format document ingestion (PDF, images, scans); Intelligent data extraction with LLMs; Business rule validation and exception flagging; Integration with accounting, CRM, and ERP systems; Continuous learning from corrections
Deliverables: Document processing pipeline; Extraction API with structured output; Validation and exception handling system; Integration with downstream tools
Tech Stack: OpenAI, Tesseract, Python, Postgres

#### Service: AI Voice Agents (ai-voice-agents)
Status: LAUNCH | Tier: FRONTIER | Delivery: partner
Tagline: AI phone agents for bookings, support, and follow-ups
Summary: AI-powered voice agents that handle phone bookings, customer support calls, and outbound follow-ups with natural conversation abilities.
Full Description: We deploy AI voice agents that handle real phone interactions — booking appointments, answering support questions, and making outbound follow-up calls. Built on leading voice AI platforms and customized for your business context and tone.
Capabilities: Inbound call handling and routing; Appointment booking and scheduling; Customer support and FAQ resolution; Outbound follow-up and reminder calls; CRM integration and call logging
Deliverables: Deployed voice agent system; Call flow configurations; CRM/calendar integration; Quality monitoring dashboard
Tech Stack: Vapi, OpenAI, Twilio, Node.js


=== Category: AI Integration (integration) ===
Target Buyer Intent: We have an app and want AI in it
Category Description: Retrofitting AI capabilities into your existing software — search, summarization, recommendations, and model orchestration without rebuilding.

#### Service: AI Integration Retrofits (ai-integration-retrofits)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Bolt AI features onto your existing product
Summary: Adding AI-powered search, summarization, recommendations, and content generation to your existing application — without rebuilding from scratch.
Full Description: Your product already works. We make it smarter. We retrofit AI capabilities — intelligent search, auto-summarization, recommendation engines, content generation — into your existing codebase. No rewrite, no migration, just targeted AI enhancements that deliver immediate value.
Capabilities: AI-powered search and discovery for existing content; Automatic content summarization and tagging; Personalized recommendation engines; Smart auto-complete and content generation; Seamless integration with your existing tech stack; Progressive rollout with feature flags
Deliverables: AI features integrated into your existing app; API layer for AI capabilities; Performance monitoring and analytics; Technical documentation and team handoff
Tech Stack: OpenAI, Vercel AI SDK, TypeScript, Postgres

#### Service: AI Middleware / API Orchestration (ai-middleware-api)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Integrate AI models into your existing stack
Summary: A middleware layer that integrates OpenAI, Anthropic, Google AI, and open-source models into your existing application stack with unified APIs and fallback routing.
Full Description: We build the glue layer between AI models and your existing systems. A unified API that handles model selection, fallback routing, rate limiting, and cost tracking — so your team consumes AI capabilities through a single, reliable interface regardless of the underlying provider.
Capabilities: Multi-provider AI model integration (OpenAI, Anthropic, Google, open-source); Unified API with automatic failover; Rate limiting and cost tracking; Response caching and optimization; Provider-agnostic prompt management
Deliverables: AI middleware API; Provider configuration and routing rules; Cost tracking dashboard; Integration documentation and SDKs
Tech Stack: TypeScript, OpenAI, Anthropic, Redis, Postgres

#### Service: Fine-Tuned/Custom ML Models (fine-tuned-custom-models)
Status: LAUNCH | Tier: FRONTIER | Delivery: partner
Tagline: Purpose-built models for your specific use case
Summary: Custom-trained machine learning models for fraud detection, content recommendations, predictive maintenance, and other domain-specific applications.
Full Description: When off-the-shelf models aren't enough, we build custom ones. Fine-tuned on your data for your specific problem — whether it's fraud detection, content classification, or domain-specific language understanding. Delivered with training pipelines so you can retrain as your data evolves.
Capabilities: Fine-tuning of foundation models on your data; Custom classification and detection models; Domain-specific language model training; Automated retraining pipelines; Model evaluation and benchmarking
Deliverables: Trained custom model(s); Inference API; Training and retraining pipeline; Model evaluation reports
Tech Stack: Python, PyTorch, Azure AI, MLflow


=== Category: AI-Native Development (development) ===
Target Buyer Intent: Building AI-native from scratch
Category Description: Full-stack software builds where AI is a core architectural decision — not an afterthought. Custom applications and MCP connectors built for the AI era.

#### Service: AI-Native Custom Software Builds (ai-native-custom-software)
Status: LAUNCH | Tier: CORE | Delivery: in-house
Tagline: Full-stack builds with AI as a core feature
Summary: Complete web applications and software systems built AI-native from day one — with intelligent features, automation, and data-driven capabilities baked into the architecture.
Full Description: We don't bolt AI onto finished products — we build software where AI is a first-class architectural decision. From the data model to the user interface, every layer is designed to leverage AI capabilities. The result is software that's inherently smarter, more automated, and more valuable than traditional builds.
Capabilities: Full-stack web application development; AI-native architecture design; RAG, agents, and automation as core features; Modern frontend with React/Next.js or Astro; Scalable backend with ASP.NET Core or Node.js; Database design optimized for AI workloads
Deliverables: Production-ready web application; AI-powered features and integrations; API documentation; Deployment and operations runbook
Tech Stack: ASP.NET Core, Next.js, OpenAI, Postgres, Azure

#### Service: Custom MCP Server Development (custom-mcp-server-development)
Status: LAUNCH | Tier: FRONTIER | Delivery: in-house
Tagline: Custom Model Context Protocol connectors
Summary: Purpose-built MCP (Model Context Protocol) servers that give AI models structured access to your internal systems, databases, and APIs — an early-mover, low-competition space.
Full Description: MCP is the emerging standard for connecting AI models to external tools and data. We build custom MCP servers that give Claude, GPT, and other models structured, secure access to your internal systems. This is an early-mover space with very few providers — and we're already building production MCP connectors.
Capabilities: Custom MCP server design and implementation; Secure tool and resource exposure for AI models; Integration with internal APIs, databases, and file systems; Permission and access control layers; Testing and validation tooling; Compatible with Claude, Cursor, Windsurf, and other MCP clients
Deliverables: Production MCP server; Tool and resource definitions; Security and access control configuration; Integration guide and documentation
Tech Stack: TypeScript, MCP SDK, Node.js, Postgres


=== Category: AI Strategy & Consulting (strategy) ===
Target Buyer Intent: We don't know where to start
Category Description: Feasibility studies, process audits, and implementation roadmaps that cut through the AI hype to find real opportunities in your business.

#### Service: AI Strategy / Opportunity Assessment (ai-strategy-assessment)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: A clear roadmap before any build begins
Summary: Feasibility studies, build-vs-buy analysis, and phased implementation roadmaps that tell you exactly where AI can drive value in your business — and where it can't.
Full Description: Before writing any code, we help you figure out what to build. Our AI strategy assessments cut through the hype to identify real, high-impact AI opportunities in your business. You leave with a prioritized roadmap, clear cost estimates, and honest build-vs-buy recommendations — not a slide deck full of buzzwords.
Capabilities: AI opportunity identification and feasibility analysis; Build vs. buy recommendations for each use case; Phased implementation roadmap with cost estimates; Data readiness assessment; Vendor and technology evaluation; Risk assessment and mitigation planning
Deliverables: AI opportunity assessment report; Prioritized implementation roadmap; Build-vs-buy analysis per use case; Data readiness scorecard
Tech Stack: Strategy, Analysis, Workshops, Documentation

#### Service: AI Process Audits (ai-process-audits)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: Find where AI can save you money
Summary: Paid discovery engagements that audit your operations to identify where AI can reduce costs, speed up processes, or improve quality — with ROI estimates for each opportunity.
Full Description: We embed with your team for a focused sprint to map your operations and identify the highest-ROI AI automation opportunities. Each finding comes with an implementation estimate, expected savings, and a clear recommendation on whether to build, buy, or skip.
Capabilities: Operational process mapping; AI automation opportunity identification; ROI estimation per opportunity; Implementation effort sizing; Quick-win vs. strategic initiative classification
Deliverables: Process audit report; Prioritized automation opportunities; ROI estimates per opportunity; Implementation recommendations
Tech Stack: Process Analysis, Workshops, Documentation

#### Service: AI Training/Enablement (ai-training-enablement)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: Make sure your team actually adopts the AI tools
Summary: Workshops and hands-on training so your staff actually uses the AI tools built for them — because the best system is worthless if nobody adopts it.
Full Description: The biggest risk in any AI project isn't the technology — it's adoption. We run hands-on workshops and onboarding programs that get your team comfortable and productive with new AI tools, custom-tailored to your specific workflows and systems.
Capabilities: Custom workshop design for your tools and workflows; Hands-on training sessions (remote or on-site); AI literacy programs for non-technical staff; Power-user and admin training tracks; Adoption tracking and follow-up support
Deliverables: Custom training curriculum; Workshop materials and recordings; Quick reference guides; Adoption tracking report
Tech Stack: Training, Workshops, Documentation


=== Category: Quick-Start AI (quick-start) ===
Target Buyer Intent: Something simple, fast
Category Description: Lightweight AI solutions you can deploy quickly — chatbots, LLM integrations, and content tools that deliver value in days, not months.

#### Service: Lightweight AI Chatbot Deployment (lightweight-ai-chatbot)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: Website chatbots and messaging bots — fast
Summary: Quick-deploy AI chatbots for your website, WhatsApp, or Slack — simpler than full RAG, faster to launch, and great for FAQ handling and lead capture.
Full Description: Not every AI project needs a full knowledge system. We deploy lightweight chatbots that handle common questions, capture leads, and route complex requests to your team. Live in days, not months.
Capabilities: Website chat widget deployment; WhatsApp and Slack bot integration; FAQ handling with AI-powered responses; Lead capture and qualification; Human handoff for complex queries
Deliverables: Deployed chatbot on your channels; Content and response configuration; Analytics dashboard; Handoff integration
Tech Stack: OpenAI, TypeScript, Node.js

#### Service: LLM API Integration Consulting (llm-api-consulting)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house
Tagline: Choose and wire up the right AI model for your needs
Summary: Expert guidance on selecting and integrating the right LLM — OpenAI vs. Claude vs. Gemini vs. open-source — for your specific use case, budget, and constraints.
Full Description: The AI model landscape changes monthly. We help you cut through the noise — evaluating models against your actual requirements (cost, latency, accuracy, data privacy) and wiring the winner into your stack with proper error handling, fallbacks, and cost controls.
Capabilities: Model evaluation and benchmarking for your use case; API integration with best practices; Cost optimization and usage monitoring; Prompt engineering and optimization; Fallback and error handling strategies
Deliverables: Model evaluation report; Working API integration; Prompt library and guidelines; Cost monitoring setup
Tech Stack: OpenAI, Anthropic, Google AI, TypeScript

#### Service: AI Content/SEO Tooling (ai-content-seo-tooling)
Status: LAUNCH | Tier: FOUNDATION | Delivery: in-house-partner
Tagline: AI-powered content generation for marketing
Summary: AI content generation and personalization tools for marketing sites — automated blog posts, product descriptions, SEO optimization, and content A/B testing.
Full Description: We build AI-powered content pipelines that help your marketing team produce more, better content — from automated first drafts to SEO optimization suggestions and personalized content variants. Integrated into your existing CMS and publishing workflow.
Capabilities: AI-assisted content generation and editing; SEO optimization and keyword analysis; Content personalization and A/B testing; CMS integration for automated publishing; Brand voice consistency enforcement
Deliverables: AI content generation tools; CMS integration; SEO analysis dashboard; Content team training
Tech Stack: OpenAI, Next.js, TypeScript, Vercel

## 8. Frequently Asked Questions
Q1: Who owns the IP and code you build?
A: You do — fully. Every engagement transfers all source code, model artifacts, prompts, and documentation to your organization. We retain no rights and create no dependency on us to keep the system running.

Q2: How do you handle our data?
A: We follow strict data handling practices. Your data is used only for your project, never shared with other clients, and never used to train third-party models. We're happy to sign NDAs and DPAs as needed.

Q3: What does a typical timeline look like?
A: An AI Strategy Assessment runs 1-2 weeks and ends with a roadmap. A Focused Build typically ships a production system in 4-12 weeks depending on complexity. Full AI-native product builds run 8-16 weeks. We scope precisely before committing.

Q4: How do you integrate with our existing team?
A: We work in your tools and workflows — your repos, your ticketing, your standups. Our engineers collaborate with yours so knowledge transfers rather than concentrates. The goal is a team that can maintain and extend the system without us.

Q5: What AI models and platforms do you use?
A: We're model-agnostic. OpenAI, Anthropic (Claude), Google (Gemini), and open-source models like Llama and Mistral — we choose based on your requirements for cost, quality, latency, and data privacy. We can also switch models later without rebuilding.

Q6: How do you measure success?
A: Every project defines success metrics up front — user adoption, accuracy, time saved, cost reduction. We build measurement into the system from day one, so results are tracked, not asserted.

## 9. About dyta.ai
Company: A small team building big AI capabilities.
Description: dyta.ai is a focused team of engineers who build AI-powered software. We handle the full stack — from strategy to production — so you get AI as a real capability, not a buzzword.
Coverage: Global (remote-first, worldwide delivery)
Founded: 2026
IP Policy: 100% client code & IP ownership guaranteed
GitHub: https://github.com/dyta

## 10. How to Engage
1. Visit https://dyta.ai/contact/ or email hello@dyta.ai
2. Describe your project, constraints, and goals
3. Receive a technical point of view (not a sales deck) within 48 hours
4. If there's a fit, we scope precisely before committing

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Last updated: 2026-07-20