01
SMBs going AI-first
You know AI should be in your product or operations, but you don't have an in-house AI team. We become your AI engineering arm.
/indexAI-NATIVE WEB & SOFTWARE SOLUTIONSdyta.ai
2 project slots open for Q3
// MOST AGENCIES BOLTED AI ON. WE DIDN'T.
Built AI-native.
From the ground up.
We engineer custom RAG systems, autonomous workflow agents, and fine-tuned models that cut operational latency by 80% and scale throughput without adding headcount — with 100% IP ownership.
What Happens Next:
1. 30-min Call
2. AI Map in 48h
3. Fixed Proposal
4. Project Kickoff
// ARCHITECTURE_TRANSFORMATIONLIVE
[Data Layer]Siloed
Manual SQL queries, fragmented spreadsheets, slow keyword search.
[Workflows]Manual
Humans doing repetitive copy-paste and manual data entry.
[Intelligence]Bolt-on Demo
Generic ChatGPT wrapper slapped onto legacy code.
[RAG Knowledge Base]Instant
Hybrid vector + keyword search over your proprietary data.
[Autonomous Agents]24/7 Exec
Multi-step task automation & tool calling via custom MCP servers.
[Full IP Handoff]100% Owned
All code, prompts, models, and docs transferred directly to you.
Result: 10x Velocity + Zero Vendor Lock-inExplore →
Why Dyta
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.
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.
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.
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.'
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.
Who We Work With
Built for teams that want AI as a capability, not a buzzword.
02
Mid-market scaling AI
You've done a proof of concept or two. Now you need production-grade systems that scale, with proper evaluation and monitoring.
03
Teams with existing software
Your product works — it just needs to be smarter. AI search, recommendations, automation, or agent features added to your existing stack.
Proof Point
Case Study 01: Production AI in action.
A look inside one of our flagship builds — built with the exact stack and methodology we bring to clients.
FEATURED BUILD|Internal Platform // Dyta Engine
STATUS: DEPLOYED / PRODUCTION
Enterprise Knowledge & RAG Assistant Platform
// The Problem
500+ unorganized technical documents and internal manuals causing high latency in engineering onboarding and customer support responses.
// The Solution
Built a custom, model-agnostic RAG engine featuring hybrid vector/keyword search, role-based access controls, and automated document ingestion pipelines.
TECH STACK:
AstroPythonFastAPIQdrantVercel AI SDK
// Measurable Outcomes
Query latency< 400ms
Sub-second response
Search efficiency+85%
Faster document retrieval
Data privacy100%
Zero 3rd-party model training
How We Work
A clear path from problem to production.
Every engagement follows the same disciplined process. No black boxes — each stage produces a concrete, tangible deliverable.
Discover
Understand your problem, data, constraints, and goals. Map the opportunity landscape.
Deliverable:Opportunity Map + AI-Readiness Score
Design
Architecture, AI strategy, and solution blueprint. Clear specs before any code is written.
Deliverable:Technical Spec + Prototype Scope
Build
AI-native development with continuous demos, evaluation, and feedback loops.
Deliverable:Production Code + Eval Suite
Launch
Production deployment, documentation, team handoff — and optional ongoing support.
Deliverable:Deployed System + 100% IP Handoff
Service Directory
Explore the capability tree.
~/dyta.ai/services
The Stack
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
- GPT-4o / GPT-4.1
- Claude (Anthropic)
- Gemini (Google)
- DeepSeek
- Llama / Mistral
- Fine-tuned models
Frameworks & Tooling
- LangChain / LangGraph
- Vercel AI SDK
- MCP Protocol
- LlamaIndex
- Semantic Kernel
- pgvector
Application Stack
- ASP.NET Core
- Next.js / React
- Astro
- Node.js
- Postgres
- Redis
Delivery & Ops
- Azure / AWS
- Docker
- GitHub Actions
- Vercel
- Monitoring
- CI/CD pipelines
Trust & Quality
AI done right means AI you can trust.
We build AI systems the way serious engineering should work — measurable, documented, zero third-party model training, and fully yours when the project ends.
Our commitments
Full IP TransferSource Code HandoffZero Model TrainingPII Filtering & Data MaskingSOC 2 / HIPAA AlignmentEvaluation Suites
You own everything
All source code, model artifacts, prompts, and documentation transfer to your organization. No lock-in, no proprietary dependencies.
Enterprise security & privacy
Client data is never trained on by third-party models. Built with isolated vector database namespaces, automated PII data masking, role-based access control (RBAC), and SOC 2 / HIPAA boundary readiness.
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.
Verified Client Outcomes
What engineering leaders say about our builds.
Direct feedback from CTOs, Founders, and VPs of Operations who partnered with dyta.ai for production AI systems.
RAG & KNOWLEDGE ASSISTANT< 400ms Latency
"dyta.ai reduced our internal technical document search overhead from 45 minutes to sub-400ms retrieval while guaranteeing zero third-party model training on our proprietary IP."
VP of Operations
Mid-Market Logistics & Supply Chain
AI AGENT AUTOMATION+85% Ops Efficiency
"They delivered a complete LangGraph agent automation suite in 3 weeks, transferred 100% of the source code and evaluation suites, and enabled our team to extend it independently."
Founder & Lead Architect
B2B SaaS Platform
CUSTOM MCP & INTEGRATION0 Legacy Disruptions
"The custom Model Context Protocol (MCP) server retrofitted our legacy SQL database without disrupting a single existing API endpoint. Outstanding senior engineering quality."
VP of Engineering
Enterprise Financial Services
Executive Risk Clearance
Solving silent objections before code is written.
Production AI projects fail when security, legacy integration, or vendor lock-in are ignored. Here is how we guarantee safety across every build.
DATA PRIVACY
"Will our proprietary data or IP train third-party public AI models?"
✓ Zero Third-Party Training Guaranteed.
We enforce enterprise zero-retention API endpoints, isolated vector database namespaces, and automated PII data masking before any prompt payload reaches an LLM model.
TECH DEBT & INTEGRATION
"Will an AI build require rewriting our existing software stack?"
✓ Decoupled Architecture & Retrofits.
We build AI middleware microservices and custom Model Context Protocol (MCP) servers that plug into your existing ASP.NET, Node, Python, or SQL databases via REST/gRPC without touching legacy core code.
IP OWNERSHIP & HANDOFF
"What happens to the code, models, and docs when your team leaves?"
✓ 100% Client IP Handoff & Independence.
All source code, fine-tuned model weights, prompt engineering suites, CI/CD pipelines, and architectural docs transfer directly to your GitHub/cloud tenant. Your team maintains total long-term independence.
Buyer Decision Matrix
How dyta.ai compares to alternatives.
Production AI requires specialized architecture, evaluation suites, and data safety guarantees. Here is how our founder-led studio compares to traditional options.
| Evaluation Criteria | dyta.ai (Founder-Led) | Freelancers | Generic Agencies | DIY No-Code Tools |
|---|---|---|---|---|
| IP & Code Ownership | ✓100% Full Source Code & IP Handoff | Variable / Unclear licensing | Often tied to proprietary retainers | Zero code ownership (Platform lock-in) |
| Engineering Expertise | ✓Senior AI Engineers & Founder Oversight | Single developer capacity limits | Delegated to junior dev teams | Non-technical drag-and-drop |
| Enterprise Data Privacy | ✓Zero 3rd-Party Training & PII Filters | Basic API key usage | Standard shared API endpoints | Data passes through 3rd-party webhooks |
| Architecture Depth | ✓Sub-400ms RAG, Agents & MCP Servers | Basic ChatGPT wrapper scripts | Generic web apps with AI bolted on | Fragile automation workflows that break |
| Pricing & Handover | ✓Fixed Scope + Complete Eval Suites | Hourly rate creep & no documentation | High monthly overhead retainers | Escalating per-execution SaaS costs |
$ // DISCUSS YOUR AI PROJECT
Ready to make your product AI-native?
Tell us what you're building and where AI could make the biggest difference. We'll respond with a technical architecture point of view within 24 hours — not a generic sales deck.
🔒 You own 100% of all code, prompts, models, and architecture. Zero vendor lock-in.