AscentCore Insights HUB

AscentCore Insights & Insights HUB

Leave the deterministic steps to the deterministic executor.

Insights is a no-code AI automation platform where every business process becomes a governed, repeatable pipeline — built visually, orchestrated through one hub, and run inside your own infrastructure. Reasoning where you need it. Determinism where you don't.

90+ ready-to-use operations On-premise or your own cloud Multi-LLM cost routing Full audit on every run

Don't pay a reasoning model to re-think the same task 10,000 times. Fix the plan once — then let it run.

Insights HUB · The Orchestrator

One governed hub for every AI initiative

The HUB is where orchestrations live. Chain MCP calls, decision branches, AI steps, and coding agents into a single flow that runs on schedule or on demand — with parallel branches that run together and results that route themselves.

  • Orchestrate everything — workflows, skills, agents, MCP servers, Claude Code & Codex — through one interface
  • Branching logic: route on conditions like "if security issues are reported" without touching code
  • Real-time run status and history: every step shows what it is and what it did
  • Your identity, your rights — every action runs under the user's own credentials, always traceable
Insights · Workflow Builder

Build the pipeline once. Validate it once. Trust it forever.

Drag blocks onto a canvas and connect them into a Directed Acyclic Graph. Data flows deterministically from node to node — the same inputs always produce the same structured output. No drift, no surprises, no re-planning on every run.

  • Visual, no-code canvas — domain experts build their own automations, not just engineers
  • Deterministic by design: suitable for finance, compliance, QA, and operations
  • Iterator & Aggregator patterns process millions of rows, then stack the results
  • Publish as a scheduled job, REST API, chatbot, or Slack command
Skills & Connectors

Govern every credential, tool server, and skill in one place

Vault-backed credentials are leased to a workflow only for the duration of a run and revoked the moment it ends — credentials are never at rest. The same connectors power both the HUB and Insights workflows.

JIRA Project & issue trackingConfigured
GitHub Source code hostingConfigured
LiteLLM LLM proxy gatewayConfigured
JAMA Requirements mgmt
Jenkins CI/CD automation
Confluence Documentation
SFTP Secure file transfer
SSH Remote shell exec
OpenAI Language model API
Claude Anthropic AI model
Gemini Google AI model
Glean Enterprise search MCP

Plus a growing catalog of MCP servers and reusable skills — registered once, reused everywhere, monitored for health in real time.

The Operations Library

90+ building blocks. Every step of a process, ready to drop on the canvas.

When you add a step, you pick a category and an action. Each block is documented, versioned, and does exactly one thing — deterministically. Here's what the library covers.

Data Sources & Import

Bring any data in

Load documents, call any REST API, scrape pages, or read straight from your systems of record.

Load DocumentsAPI CallRead Web PageGitHub ReadConfluence ReadGoogle DocsSFTPSQL Get Data

AI & Agents

Reasoning, exactly where you need it

Embed an LLM at any node, run coding agents, add RAG memory, or call registered agents and MCP tools.

AI Action (LLM)AI ExecutorAgent CallMCP Tool CallMemoryNamed Entity RecognitionRun AI Prediction

Process & Transform

Shape data deterministically

Filter, dedup, merge, split, chunk, and reshape — pure, repeatable operations with no model in the loop.

Filter DataDeduplicateMergeCompare Side-by-SideExtract Using PatternCustom Python

Jira & Integrations

Read & write your tools

The deepest Jira coverage in the library — read, write, transition, link, and manage R4J & XRay — plus Jenkins CI/CD.

Jira Read / WriteUpdate StatusBulk OperationsR4J SuspectsXRay Test StepsJenkins
〈〉

Code Analysis

Understand change & risk

Clone, search, and diff repositories, then run dependency impact analysis and CVE scans at a fraction of agent cost.

Git CloneCode SearchCode DiffCode RippleImpact Report

Logic & Control

Branch, loop, decide

Conditionals, iterators, jumps, state variables, and human-in-the-loop review — the flow control that makes runs predictable.

ConditionalRepeat For EachCollect ResultsManual Review StepVariablesJump To Step

Testing & QA

Requirements to test cases

Generate structured, traceable test cases from requirements — with deterministic coverage planning and Figma vision grounding.

Generate Test CasesTest Cases w/ PlannerFigma Vision Analysis
🔎

Search & Knowledge

RAG over your data

Build a vector or knowledge-graph index from your own content, then query it semantically inside a workflow.

Build Search LibrarySearch In LibraryChunk Text

Results & Output

Deliver the outcome

Export files, generate Markdown reports, publish REST endpoints, or email results — the last mile of automation.

Generate ReportSave As FileSend EmailAPI TriggerEndpoint Response
Proof in production

Pay only for the AI that earns its place

Trailing-30-day usage from a live enterprise deployment. Most steps run on local models at zero inference cost — premium models are reserved for the work that truly needs them.

40+
automations built & running unattended
~2K
workflow runs / month across teams
6M
steps executed — 5.9M+ at $0
~$4.70
total premium-AI spend for the month
The core advantage

An autonomous agent re-thinks. A deterministic executor just runs.

Both have a place. The trick is knowing which to use where — and Insights lets you use both in the same flow, sending reasoning to an agent only when the task genuinely needs it.

An autonomous agent, every request

Re-plans · re-pays · re-decides
  • Re-plans from scratch: what do I need, where is it, how do I get it
  • Burns premium tokens on thinking — every single run
  • Can decide differently each time — unpredictable output
  • Limited by what it can hold in memory at once

An Insights workflow

Plan once · run forever · fully audited
  • The plan is fixed once, when it's built
  • Every run follows the same path — no re-thinking, no re-paying
  • Same input, same output, every time — fully auditable
  • Goes straight to the source and fetches exactly the right data

Reasoning is expensive. Repetition should be free.
Leave the deterministic steps to the deterministic executor.