Experience the Future of AI with Custom Large Language Models

Absolutely! At TechAhead, we can create language models that understand and respond in multiple languages. All we need is enough relevant data for each language we want the model to learn.

Fine-tuning takes a ready-made model and tweaks it with special data. Training from scratch starts with nothing and builds a whole new model using raw information. Both methods shape AI to do specific jobs.

At TechAhead, pricing is based on project complexity, data volume, model size, and development effort.

In-context learning improves Large Language Model performance by incorporating additional context during training, enhancing the model's understanding and its reasoning capabilities.

Yes, we can create optimized versions of custom LLMs specifically for mobile devices, taking into account the constraints and limitations of mobile hardware. This ensures that the language models perform efficiently on mobile platforms while delivering the desired functionality and user experience.

Contact us for a free consultation to explore how a custom language model can tackle your specific problems, streamline operations, boost productivity, and drive growth. Let's discuss practical solutions tailored to your unique business needs and goals.

Custom LLM costs vary based on three main factors: how big your project is, how much data you need to process, and what features you want built in. While there's an upfront investment to create your own model, you'll typically spend less money over time since you won't be paying API fees for every request like you do with third-party services.

Contact us to discuss your needs. We'll examine your requirements, understand your constraints, and design a solution that works. Our approach is straightforward: identify the real issue, map out what you have to work with, then build a practical plan to get you where you need to be.

Most projects require thorough preparation and model development. The duration varies based on complexity and unexpected challenges that arise during implementation. Data preparation is a crucial first step that significantly impacts overall success. Simpler projects may progress more quickly, while complex ones demand additional time and resources to achieve proper solutions and desired outcomes.

We use top AI models including GPT-3, Llama, Mistral, and BERT to solve your specific problems. Each model has unique strengths - some excel at writing, others at analysis or understanding text. Instead of forcing one solution everywhere, we pick the right AI tool for your particular challenge, ensuring you get the most effective results for your situation.

We provide on-site and private cloud options so you keep complete control of your data and meet all compliance requirements. Your information stays exactly where you need it - whether that's on your own servers or in a dedicated private cloud environment. This ensures you maintain full security, privacy, and regulatory compliance while getting the solutions you need.

We connect AI language models directly into your existing business systems - whether that's your customer management software, business operations platform, or custom workflows. This integration eliminates data silos and manual work, letting AI automatically handle tasks like customer inquiries, data processing, and workflow automation right within your current setup for seamless daily operations.

We handle all the compliance headaches for you. Whether you need GDPR for data privacy, HIPAA for healthcare, or SOC 2 for security - we've got it covered. No need to worry about regulations or audits. Your solution automatically meets every requirement, so you can focus on your business instead of paperwork and legal complexities.

Most clients see a working POC in 3–4 weeks and move to production in 8–12 weeks.

We deliver plug‑and‑play SDKs and secure APIs for Salesforce, HubSpot, Dynamics 365, Zendesk, ServiceNow, and any in‑house CRM/ERP built on REST or GraphQL.

Projects combine a one‑time build fee plus a predictable run‑rate. FinOps dashboards track GPU usage so operating spend stays 40–60 % lower than public AI APIs.

Your model runs in a private VPC or on‑prem cluster with encryption at rest/in transit, SOC 2 controls, and options for HIPAA, GDPR, and PCI alignment.

Our LLM‑Ops stack tracks accuracy drift, latency, and cost per query. One‑click retraining keeps quality on target and budgets in check.

Clients typically realise a 5–10× payback via faster workflows, higher conversion, or lower support costs within the first 12 months.