Ask.AI

A unified AI platform that searches across scattered enterprise data and turns customer conversations into actionable analytics for B2B teams.

Services

Dedicated Development Team

Client

Ask.AI

Location

Texas, USA

Industry

Custom Software Development Tools for IT Professionals

Results

16+

enterprise data sources integrated

70%

faster onboarding for new connectors

4

unified authentication models

Team

Technologies

Python

TypeScript

Express.js

ReactJS

PostgreSQL

ElasticSearch

Firebase

Google Cloud Platform

Google Vertex AI

Amazon Web Services

Docker

Terraform

Pytest

Cypress

Unified Integration Catalog

A self-serve panel inside the portal where customers add data sources through a guided setup flow. Every connector runs on the same shared framework so ingestion, refresh, and error handling stay consistent across the catalog.

Supports OAuth 2.0, API key, credentials, and login flows
Live source health checks before activation
Per-source scope selection for ingested data
Automatic token refresh and pagination handling

Cross-Source AI Search

A search interface that answers natural-language questions across every connected workspace, ticketing, and knowledge tool. Every answer links back to the exact source document so users can verify context without switching apps.

Source-scoped queries with user-selectable inclusion
Chrome extension for search at point of work
Vertex AI grounding across indexed content
Full-text and semantic retrieval via Elasticsearch

Customer Intelligence Mosaics

An analytics layer that turns raw customer conversations into themes, trends, and tracked initiatives for product and CX teams. Data flows in from support tickets, chats, and interviews across every connected source.

Trend detection across support tickets and chats
Initiative impact tracking over rolling windows
Drill-down from theme to source conversation
BigQuery-backed aggregation for large-scale analysis

Microservices Backbone

A distributed backend of around 25 services handling ingestion, transformation, search, and analytics independently. Each service owns its data model, deploy cycle, and failure boundary.

Independent Cloud Run deploys per service
Terraform-declared infrastructure across environments
Workload-split data layer across four storage engines
Cloud Functions for lightweight event handlers

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CHALLENGES & SOLUTIONS

During our work on this project, we've faced a lot of complicated challenges. We believe that each challenge has a solution. See yourself!

Challenge #1

Fragmented authentication flows

Solution #1

A shared integration framework that abstracts OAuth 2.0, API key, credentials, and login flows behind one connector contract.

Challenge #2

Long onboarding for new sources

Solution #2

A 4-step delivery playbook that turns each new connector into a repeatable cycle.

Challenge #3

Unstable third-party APIs

Solution #3

Per-source adapters with isolated retry, rate-limit, and pagination logic.

Clients say

With Incora's support, we were delivered a polished console experience and quickly iterate new features to market. We have been very impressed with the level of Incora's communication. In my previous experience, this has been one of the biggest challenges in working with off shore development teams, but everyone we have worked with at Incora has had impeccable communication skills, both written and on Zoom calls.

Lucas McGrew

Co-founder & CIO at Sumatra

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