Skip to main content
BiltIQ AI logoBiltIQ AI logo
AI Orchestration · Workflows
ATC

Flow

Automated Intelligence Workflows.

MCP-Powered
Data Processing Pipelines.

Continuous data processing with MCP protocol. Scrape, process, transform, and deliver fresh intelligence daily — powered by local LLMs on your GPU infrastructure. No per-token API costs. No cloud dependency.

60–70% cost reduction vs cloud API workflows. Your data pipeline runs on your electricity, not someone else’s cloud.
70%
Cost Reduction
24/7
Pipeline Uptime
0
Per-Token Fees
Automate Your Data Pipeline
Show us your manual workflow. We'll build an automated Flow pipeline and demo it on your infrastructure.
Your data stays private. We never share your information.

Automate Your Intelligence Pipeline

Show us your manual data workflow. We’ll build an automated Flow pipeline and demo it live — on your infrastructure, with your data.

Book Consultation →+91 8986860088

Your Data. Your Premises. Your AI.

FAQ

Frequently Asked Questions

How is ATC Flow different from Zapier or Make?

Zapier and Make trigger pre-built integrations on cloud APIs; ATC Flow runs entire data pipelines on your infrastructure, including the LLM step. No per-action pricing, no cloud egress, custom MCP tools.

How is ATC Flow different from your AI Workflow Automation service?

ATC Flow is the productised data-pipeline platform — installable in days, scoped to MCP-orchestrated processing jobs. The Workflow Automation service is a custom engagement where we design end-to-end agent-based workflows for your specific approvals, escalations, and audit needs. Most customers buy both.

Where does the 60–70% cost reduction come from?

Replacing per-token cloud LLM API calls with local LLM inference on amortised GPU hardware. For workflows above ~5M tokens per month, on-prem inference breaks even within 6 to 9 months.

What kinds of pipelines do customers build?

News and competitor monitoring, financial filings extraction, supplier price scraping, document intake and classification, internal report generation, and data-quality checks across multiple databases.

How are jobs scheduled?

Cron, event-based, or webhook-triggered. Job graphs support fan-out, fan-in, retries with exponential backoff, and dead-letter queues. Observability via Prometheus and Grafana dashboards.

Does ATC Flow handle structured outputs reliably?

Yes. JSON-mode generation with schema validation, automatic retries on parse failure, and grammar-constrained decoding for strict-format outputs (XML, SQL, regex-bounded tokens).

Can pipelines call external APIs?

Yes — outbound is allowed for explicitly whitelisted endpoints, audited per call. Most customers route external calls through a single network DMZ for centralized auditing and rate-limiting.

What is the operational footprint?

A single H100 GPU plus 8 vCPU control plane handles ~10,000 LLM-step jobs per day with redundancy. Storage scales with raw data and intermediate outputs.