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Case Study · 04

Khove — your tools, finally thinking together.

An AI-native workspace that puts GitHub, Google Calendar and Jira behind a single conversational interface, so you can plan, track and ship without switching tabs. Ask in plain English; Khove routes the request, pulls context across every tool, and takes the action.

Web platform Conversational
Khove landing page
Role
Founder
Timeline
2026 — present
Type
AI-native developer tooling
Status
Live
01 — Overview

Context lives in three tabs. Nobody's job is stitching it together.

An engineer's day is spread across a repo, a calendar and a tracker, and the answer to "what needs my attention" exists in none of them alone. It exists in the overlap, which a human has to assemble by hand, every morning.

Khove collapses that. It reads across GitHub, Google Calendar and Jira, answers in one place, and then acts: opening issues, creating tasks, blocking time. The distinction matters: most tools stop at the summary. Khove is built so the answer comes with the action attached.

It's an agent product, not a chat wrapper. Every request maps to a real, workspace-scoped tool call, and the hard engineering sits in permissioning, memory, and knowing which model to spend on.

02 — What it does
One
Conversational interface across every connected tool
Acts
Creates tasks, opens issues, books time, not just answers
Forecasts
Projected finish, velocity and days late per initiative
Memory
Persistent context carried between conversations
Teams
Workspace-scoped integrations, shared memory and standups
03 — Decisions that mattered

Where the engineering actually went.

01
Workspace-scoped everythingEach workspace connects its own accounts with encrypted tokens. No shared credentials, no cross-tenant leakage: the thing that makes team adoption survivable.
02
Intent → tool call, not intent → textBuilt the routing layer that maps a plain-English ask onto a concrete, permissioned action across the connected stack.
03
A cost-aware model routerSimple asks go to a fast model, hard ones to a stronger one. Users get speed without paying for frontier inference on every trivial question.
04
Memory as a product featurePersistent memory learns working preferences and stops re-asking setup questions: the difference between a demo and a daily habit.
05
Integrations free on every tierPricing charges for AI actions, not for connecting tools. Removes the adoption barrier that kills most integration products.
06
Read across, then offerKhove proposes the action and waits for confirmation, and the conversation shows every tool call it made to get there. Agentic, but auditable: essential when it has write access to real systems.
07
Forecasting, not reportingInitiatives carry target dates; Khove folds GitHub merges into a burn-up, projects a finish date, computes days late, and writes the narrative explaining the risk.
08
Metrics a lead reports onThroughput, cycle time, review latency, deploys, stale in-progress work and sprint burndown, derived across GitHub and Jira rather than read from either.
04 — Frameworks & stack

The toolkit behind Khove.

AI & agents

LLM tool-callingModel routingPersistent memoryIntent parsingConversational UX

Platform

Next.jsTypeScriptOAuth 2.0Encrypted token storageMulti-tenant workspacesWebhooks

Integrations

GitHubGoogle CalendarJira

Product surface

Consolidated dashboardsDelivery forecastingSprint intelligencePlanner & calendarStandup automationAdmin dashboard
05 — Screens

Inside the product, screen by screen.

Five surfaces, each solving a different part of the same problem: the answer to “what needs my attention” lives in the overlap between three tools, and nobody's job is assembling it.

Khove consolidated dashboard showing GitHub and calendar KPIs
Screen 01 · Dashboards

Three systems resolved into one KPI surface

A single dashboard, “Consolidated Platform First”, carrying merges, weekly throughput, cycle time, review latency, open PRs and deploys from GitHub, next to upcoming deadlines, today's schedule and overdue items from Google Calendar.

Every tile shows a delta against the previous 28 days, so the dashboard reports direction, not just state. Auto-refresh is on; dashboards are user-composable, and this one is starred as the default.

Why it matters: the overdue column, eight ceremonies and reviews 61–64 days stale, is exactly the signal that no single tool surfaces on its own.

Khove agent answering with a seven-step tool-call trace
Screen 02 · Chat

The agent shows its work before it answers

Asked “How are the state of things”, Khove expands seven traced steps: listed threads, checked sprint status, assessed delivery risk, measured delivery flow, cross-checked Jira against GitHub, checked for unplanned work. Then it writes a Workspace Status summarising six active connectivity threads and sprint state.

Each step is a real, permissioned tool call, not a rendering of one model response.

Why it matters: an agent with write access to production systems has to be auditable. Exposing the call trace is a trust decision, not a UI flourish.

Khove delivery forecast for an initiative, with burn-up and days late
Screen 03 · Delivery

Forecasting, not reporting

Threads with a target date become initiatives. Khove folds GitHub merges into a burn-up against that target and derives progress, velocity, projected finish and days late. Here, a platform thread is projected to land 46 days late.

The “What's happening” panel writes the narrative in prose and names the evidence: two linked tickets with code work but no pull requests attached, which is why it can't confirm completion.

Why it matters: status tools tell you where you are. This one tells you where you'll end up, and which missing link makes it uncertain.

Khove Jira dashboard with flow metrics and sprint burndown
Screen 04 · Jira

Jira as flow, not as a board

The connected project (14 open, 40 total) rendered as the metrics a lead actually reports on: completed, throughput, cycle time, points done, open bugs and stale in-progress work, with To Do / In Progress / Done counts beneath.

Sprints appear side by side: an active sprint 39 days over at 67% of issues, next to an upcoming one at 0%, each with a burndown of remaining issues against ideal.

Why it matters: “stale in-progress: 5” is a derived metric. Jira stores tickets; it doesn't tell you which ones have quietly stopped moving.

Khove planner month view synced with Google Calendar
Screen 05 · Planner

Planning where the shipping happens

A month view synced two-way with Google Calendar: daily standups, sprint planning, PR reviews, design reviews, release cutovers and personal events, filterable by meetings versus events and colour-coded by source.

Top left: fifteen agent suggestions waiting for review. Khove proposes the blocks; the human still approves them.

Why it matters: this closes the loop. The agent can read the calendar in chat, forecast against it in Delivery, and write to it here. One permission model across all three.

Khove landing page
Screen 06 · Landing page

One claim, stated once

“Your tools, finally thinking together.” The hero makes a single promise and shows the integration constellation rather than a feature list: GitHub, Calendar, Jira, Slack, Notion, GitLab, Meet, Teams, Azure orbiting the mark.

Below it: free-forever plan, no credit card, and every integration free on every tier. Pricing charges for AI actions instead.

Why it matters: integration products die at the connect step. Charging for actions rather than connections removes that barrier deliberately.

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