Agent-native database

The database
built for
autonomous agents.

KyraDB replaces fragmented database, RAG, knowledge, and tool calls with a single natural-language context query, so agents get the enterprise facts they need before they act.

See it in action Talk to the team →

Context stream

deal:ENT-2847CONTEXT_UPDATED3 new signals · confidence +0.12project:AtlasBLOCKER_INFERREDinfra approval unresolved · 14 dayspriya.sharmaCONTEXT_ENRICHEDbudget ownership confirmed · 4 sourcesQ2-roadmapDECISION_RECORDEDscope change rationale preservedvendor:AcmeSIGNAL_AGEDno signals in 47 days · confidence decayingpolicy:hire-freezeCONFLICT_DETECTED3 open reqs in conflictdeal:ENT-2847CONTEXT_UPDATED3 new signals · confidence +0.12project:AtlasBLOCKER_INFERREDinfra approval unresolved · 14 dayspriya.sharmaCONTEXT_ENRICHEDbudget ownership confirmed · 4 sourcesQ2-roadmapDECISION_RECORDEDscope change rationale preservedvendor:AcmeSIGNAL_AGEDno signals in 47 days · confidence decayingpolicy:hire-freezeCONFLICT_DETECTED3 open reqs in conflict

Backed by

Microsoft AzureCREDITS_SECURED$50K startup cloud creditsMongoDBSTARTUP_PROGRAM$5K credits secured twiceNVIDIA InceptionACCEPTEDAI startup programMicrosoft AzureCREDITS_SECURED$50K startup cloud creditsMongoDBSTARTUP_PROGRAM$5K credits secured twiceNVIDIA InceptionACCEPTEDAI startup program

Why Agents Need A New Database

Agents should query context.
Not orchestrate your stack.

Production agents maintain long-lived state, coordinate with other agents, recover from failures, and mutate shared context. Existing databases were built for applications serving humans, not autonomous execution loops.

Without KyraDB

Vector DB

RAG pipeline

Knowledge base

State store

Lock manager

Tool orchestration

With KyraDB

Ask for context

Customer history, prior refunds, company policies, enterprise knowledge, and current causal state returned together.

One context query

Agents ask KyraDB for customer, policy, transaction, refund, and enterprise context in one response.

Less orchestration code

Teams stop stitching vector search, RAG pipelines, state stores, lock managers, and tool chains into every agent.

Agent execution model

Long-lived state, shared context mutation, failure recovery, and concurrency belong inside the database layer.

Use Cases

Use cases by enterprise function
so every team sees where Kyra fits.

Designed for quick scanning by department. These are product scenarios, not invented customer claims: each function depends on sourced, temporal, durable context that ordinary RAG and single-app copilots do not preserve.

Function

Engineering

Ship with code, incident, ownership, and architecture context already assembled.

Common workflows

Incident response memory
Architecture-aware coding agents
Code review with policy and history
Runbook and documentation updates

Typical context sources

GitHubJiraLinearAWS

Supported Connectors

Out-of-the-box signals
from the tools your org already uses.

KyraDB connects to collaboration, work, CRM, code, email, support, and cloud systems so agents work from live organisational context instead of isolated prompts.

Slack

Collaboration

Microsoft Teams

Collaboration

Jira

Work

Confluence

Knowledge

Notion

Knowledge

Linear

Work

Gmail

Outlook

HubSpot

CRM

Zoho CRM

CRM

AWS

Cloud

Google Cloud

Cloud

Azure

Cloud

GitHub

Code

Salesforce

CRM

Zendesk

Support

What KyraDB Is

Database primitives
for agent execution.

KyraDB is built around the operations autonomous agents actually need: append evidence, retrieve bounded context, act with a causal token, and replay what happened.

01 —

Natural-language context query

An agent asks for customer, policy, transaction, support, or code context directly instead of issuing a chain of retrieval calls.

02 —

Immutable context log

Observations, documents, facts, and agent write-backs append to a causally ordered source of truth.

03 —

Causal token and context bundle

Every agent action can be tied to the exact bounded context it saw and the database state it acted on.

04 —

Async projections

Graph, vector, search, identity, and fact models are rebuilt from the log without touching the write path.

Signal Sources

Every signal your org produces
becomes context.

Collaboration

Conversations

Where real decisions get made, blocked, and explained.

SlackEmailTeamsMeetings

Work Systems

Tasks & Approvals

Formal workflows — and every deviation from them.

JiraLinearAsanaNotion

Revenue

Deals & Accounts

What's at risk, who owns what, where revenue is blocked.

SalesforceHubSpotPipedrive

Infrastructure

Systems & Code

Org structure, code history, telemetry, and legacy data.

HRISGitHubLogsLegacy

Context Properties

Context isn't stored.
It's earned.

Every piece of context in KyraDB must be justified, sourced, and kept current.

◎

Sourced

Every inference traces back to the signals that produced it.

◈

Weighted

Many independent signals > one. Confidence is explicit, not binary.

◷

Temporal

Context has a decay rate. Stale context surfaces as stale.

◫

Layered

Formal and inferred context are kept distinct and queryable separately.

◉

Persistent

Full lineage of how every belief formed and changed. Always accessible.

Agent Workloads

Built for agents
operating on real systems.

CRM Agents

Customer context in one query

Account history, refunds, open tickets, policies, and internal decisions are returned together before the agent drafts or updates anything.

"What should this agent know before touching the account?"

Coding Agents

Code, policy, and incident memory

Repository context, architecture decisions, prior incidents, ownership, and security constraints are assembled before a diff is proposed.

"What context justifies this change?"

Operations Agents

Stateful recovery and coordination

Incident, workflow, observability, and approval agents can coordinate over shared context instead of corrupting state with isolated tool calls.

"What changed, what already ran, and what is safe next?"

Pricing

Managed KyraDB
from developer to enterprise.

Tiers scale by managed data, context query volume, connector breadth, and enterprise deployment controls.

Feature	Developer	Team	Business	Enterprise
Managed Data	5 GB	15 GB	75 GB	Custom
Context Queries	0.2M	1M	5M	Unlimited
Connectors	2	10	50	Unlimited
HA	✗	✗	✓	✓
SSO	✗	✗	✓	✓
BYOC	✗	✗	✗	✓
SLA	✗	Standard	Priority	Custom

The databasebuilt forautonomous agents.

Agents should query context.Not orchestrate your stack.

Use cases by enterprise functionso every team sees where Kyra fits.

Engineering

Out-of-the-box signalsfrom the tools your org already uses.

Database primitivesfor agent execution.

Every signal your org producesbecomes context.

Context isn't stored.It's earned.

Built for agentsoperating on real systems.

Managed KyraDBfrom developer to enterprise.

Give your agentsone context layer. Not another chain.

The database
built for
autonomous agents.

Agents should query context.
Not orchestrate your stack.

Use cases by enterprise function
so every team sees where Kyra fits.

Out-of-the-box signals
from the tools your org already uses.

Database primitives
for agent execution.

Every signal your org produces
becomes context.

Context isn't stored.
It's earned.

Built for agents
operating on real systems.

Managed KyraDB
from developer to enterprise.

Give your agents
one context layer. Not another chain.