Automation
AI-powered solutions built for real production use
Custom AI applications, retrieval systems, and integrations—designed to be reliable, observable, secure, and aligned to business outcomes.
Custom AI applications, retrieval systems, and integrations—designed to be reliable, observable, secure, and aligned to business outcomes.
Outcome · AI features that are reliable, observable, and secure.
At a glance
What you get — in seconds
What
Intelligent systems built for production
Why it matters
Prototype AI is easy; production AI is not.
Outcome
AI features that are reliable, observable, and secure.
Why teams choose this service▾
Prototype AI is easy; production AI is not. Hallucinations, cost blowouts, and security gaps kill trust. You need architecture, evaluation, and ops discipline—not just prompt experiments.
Capabilities
What Eternix delivers
Four focused capabilities — scannable at a glance.
Use-case discovery & ROI framing
We prioritize AI features where automation or intelligence clearly beats rules-based logic.
RAG & knowledge systems
We connect your docs and data with retrieval pipelines and access controls.
Agents & workflow orchestration
We build multi-step AI workflows with human approval where needed.
Evaluation & monitoring
We measure quality, latency, and cost with test sets and production telemetry.
Process
How we work with you
- 01
Define the AI product
Success metrics, guardrails, and data boundaries before model selection.
- 02
Prototype & evaluate
Rapid experiments with benchmark tasks and red-team scenarios.
- 03
Production build
APIs, caching, auth, and fallbacks integrated with your stack.
- 04
Operate & improve
Feedback loops, prompt versioning, and model upgrades over time.
Value
Features and business impact
What we build — and what it means for your team.
- Chat and copilot experiences in your product
- Document Q&A with source citations
- Classification and extraction pipelines
- AI-assisted internal tools
- Cost and usage dashboards
- Ship AI features users can trust
- Lower risk through evaluation and guardrails
- Competitive differentiation in your product
- Foundation to expand AI use cases over time
Tech stack
Technologies we use
- OpenAI / AnthropicModel providers
- Vector DBRetrieval
- Python / NodeOrchestration
- Spring Boot / DjangoProduct APIs
Deliverables
What you receive
- Production AI feature or application
- Data ingestion and retrieval pipeline
- Evaluation suite and quality metrics
- Security and privacy review checklist
- Runbooks for prompts and model updates
Industries
Where this creates impact
- SaaS: In-app assistants and support deflection
- Knowledge work: Research, summarization, and drafting tools
- Operations: Ticket triage and routing intelligence
- Sales enablement: Proposal and CRM enrichment assistants
Case studies
Your success story goes here
We are documenting client outcomes for this service line.
Coming soon
AI Solutions project #1
Coming soon
AI Solutions project #2
FAQ
AI Solutions — common questions
Which models do you use?
We select models based on quality, cost, latency, and data policies—OpenAI, Anthropic, and open models when appropriate.
How do you reduce hallucinations?
Retrieval with citations, constrained tools, evaluation datasets, and human-in-the-loop for high-risk outputs.
Is our data used to train public models?
We configure enterprise APIs and contracts so your data stays within agreed boundaries.
Can AI integrate with our existing app?
Yes—most engagements embed AI into current Next.js, mobile, or backend products.
What does an AI MVP cost?
Scoped after discovery—focused pilots are smaller; full RAG products require more data and evaluation work.
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Ready to scope ai solutions?
Clear plan, timeline, and next steps.
- Fast scoped proposals
- Senior team, direct comms
- Clear milestone pricing