Merehead

The company's expertise includes blockchain development, complex fintech solutions, centralized and decentralized systems, and custom digital products. Merehead works with clients to shape product concepts, define roadmaps, and develop solutions intended to create business value and support growth.

Merehead also provides white-label solutions with customization options for projects that need reduced launch times and development costs.

• MVP AI chatbot for a single domain: $20,000–$40,000
• Production chatbot with integrations: $40,000–$60,000
• Multi-agent AI system: $60,000–$100,000
• Enterprise AI chatbot platform: $100,000–$150,000+

Recurring AI chatbot costs may include LLM API usage, vector database hosting, and infrastructure. The website estimates typical LLM API usage at $50–$300 per month and vector database hosting at $20–$100 per month, depending on usage and deployment requirements. Enterprise deployments with compliance requirements, audit trails, and multilingual support are scoped individually.

General project timelines

The stated implementation timeframe depends on project size and complexity: small projects may take 3–4 weeks, medium projects 2–3 months, and large or complex solutions 3–6 months.

Contact

Merehead LLC 7901 4th St N STE 300 St. Petersburg, Florida, 33702 United States

Tel.: +1 (206) 785 1688

The website invites prospective clients to discuss project ideas with a business development expert. It states that an expert will contact requesters within a few hours.

1. Concept approval: Define the project goals, target audience, and strategic vision.
2. Key features: Document the platform's functions, business logic, and technical requirements.
3. Contract: Sign an agreement covering scope, deadlines, payment terms, legal obligations, and, when needed, an NDA.
4. Development: Implement design, frontend, backend, testing, and launch preparation.
5. Launch and support: Publish the project, monitor its operation, resolve issues, and continue development.

Projects may be created from scratch or based on ready-made solutions. Merehead's technical stack includes Node.js, React.js, Go, Python, and PHP. Its mobile development department works with Swift, Kotlin, and Flutter. The company also develops microservice architectures designed for fault tolerance and scalability.

For AI chatbot projects, the process includes use-case architecture, proof-of-concept validation, data and embedding pipeline development, LLM selection, multi-agent orchestration, backend integration, deployment, monitoring, and feedback-loop development.

Production chatbot features can include persistent conversation memory, human handoff, structured tool use, permission controls, RAG-based response grounding, and multilingual support. Merehead separates the LLM layer from the business logic layer so models, retrieval logic, and agent capabilities can be changed without rewriting integrations.