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Scale your team with our experienced developers, engineers and QA experts to meet your project’s needs.

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Join a team where your ideas truly matter, and your growth is part of the culture.

Life at Focusteck is shaped by teamwork, curiosity, and a genuine drive to learn.

Why Choosing the Right AI Development Company Matters

Many organizations see promising AI results but struggle to move beyond the pilot stage. Choosing the right AI development company means gaining the right engineering, integrations, and infrastructure needed to deploy AI reliably.

Pilot Projects Stall

Many AI initiatives never move beyond proof of concept. We turn successful pilots into production-ready AI applications with scalable engineering.

Disconnected Systems

AI delivers limited value when it operates in isolation. We integrate AI with your existing software, data, and business workflows.

Fragmented Data

Poor data quality leads to inaccurate and inconsistent AI outputs. We organize, connect, and prepare enterprise data for reliable AI performance.

Scalability Challenges

What works for a small test often fails under production demand. We build AI systems designed for performance, reliability, and long-term growth.

Security & Governance

Enterprise AI requires secure access, compliance, and operational controls. We implement governance, monitoring, and security throughout the AI lifecycle.

What Our AI Consulting Services Cover

Successful AI adoption depends on more than model accuracy. Our AI consulting services focus on the engineering, integrations, and operational planning required to build secure, reliable AI systems that perform in production.

AI Modernization of Legacy Systems

Modernize legacy applications and infrastructure to support AI adoption without a costly full-system rewrite through our enterprise software services.

AI Workflow Automation

Replace manual, high-volume work with pipelines that handle unstructured input and apply judgment.

Bespoke AI Agents

Multi-step, tool-using agents that complete business processes rather than simply answering questions.

Generative AI Development Services

LLM-powered features embedded directly into your product, grounded and evaluated, not bolted on.

RAG Development

Ground model outputs in your own documents and enterprise data so responses are accurate, traceable, and reliable.

How We Approach Every Engagement

Discovery and data assessment

Usually one to two weeks, to test feasibility against your actual data before any architecture is proposed.

01

Model and architecture selection

Benchmarked against your data rather than assumed from a vendor’s marketing page.

02

Build and integration, with monitoring

Fallback paths and CI/CD built in from the first sprint rather than added at the end.

03

Deployment and ongoing observation

With drift monitoring and a defined escalation path for anything the model gets wrong.

04

Foundation Models

GPT-5, Claude Opus 4.8, Fable 5, Gemini 3, Llama 4, DeepSeek, Mistral, Gemma 4

AI Engineering

LangGraph, OpenAI Agents SDK, PydanticAI, LlamaIndex, CrewAI

MLOps & Observability

MLflow, LangSmith, Arize, Weights & Biases, PromptFoo

Evaluation & Governance

RAGAS, DeepEval, LangSmith Evals, Patronus AI, OpenTelemetry

LangGraph

Open AI

Docker

VAPI

AWS

DeepSeek

Kubernetes

LangGraph

Open AI

Docker

VAPI

AWS

DeepSeek

Kubernetes

AI

The Tech Stack We Work In

We are not a no-code AI shop. Here is a sneak peak into what is in our toolkit

Qdrant

Claude

MLflow

Pinecone

vLLM

Gemini

ElevenLabs

Qdrant

Claude

MLflow

Pinecone

vLLM

Gemini

ElevenLabs

Retrieval & Search

Qdrant, Pinecone, pg vector, Weaviate, Elastic search

Inference

vLLM, Triton, Ollama, llama.cpp

Infrastructure

AWS Bedrock, Vertex AI, Azure AI Foundry, Kubernetes, Ray, Docker, Terraform

Voice

Vapi, Twilio, ElevenLabs

Frequently Asked Questions

A chatbot is designed to answer individual questions, while an AI agent can maintain context across conversations, use external tools and APIs, and break complex goals into multiple steps before taking action. As part of our AI consulting services, we help organizations determine which approach best fits their technical requirements, business processes, and budget.

Choosing the right model is about more than benchmark scores. With our years of experience as an AI development company, help us we evaluate multiple foundation models against your own data, measuring accuracy, latency, cost per request, scalability, and data residency requirements before recommending a production architecture.

Most AI development services engagements begin with a discovery phase to define architecture, technical requirements, and success criteria. A proof of concept typically takes two to four weeks, while a production-ready deployment with integrations, monitoring, governance, and testing generally takes eight to sixteen weeks.

Yes. Our enterprise AI services are designed to integrate with existing CRMs, ERPs, databases, internal APIs, and third-party platforms. We focus on building AI that fits into your existing technology stack rather than requiring you to replace it.

Yes. As a specialized AI consulting company, we begin every engagement with a technical discovery process to understand your objectives, evaluate your data and infrastructure, identify implementation risks, and recommend the right architecture before any development starts.

Find a Solution

Tell us what you are building and we will tell you what it actually takes to ship it.

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