The Enterprise AIContext Platform

Wexa connects your data and processes into one governed context graph, so every AI agent works with full business context and your enterprise becomes AI-first, under your control.

Book a demo See how it works

The challenge

Enterprise data is scatteredAdding AI on top makes it messier and more expensive

Your enterprise
contextNo ownerSystems never connect

Salesforce

Stale

SharePointDuplicated

SnowflakeUnowned

AgentforcePartial view

Now AssistPartial view

JoulePartial view

CopilotPartial view

ChatGPTPartial view

ClaudePartial view

Paid separatelyPaid separatelyPaid separatelyPaid separatelyPaid separatelyPaid separately

The solution

One governed context graph for every AI agent

Wexa sits between enterprise systems and AI agents

Wexa unifies enterprise data and processes into governed context for AI agents. Teams build solutions, reduce token costs and accelerate AI transformation while keeping full control of the data.

Enterprise systems

Every AI agent and app

Salesforce

SharePoint

Snowflake

Any other source

ClaudeFull context

ChatGPTFull context

CopilotFull context

AgentforceFull context

Internal appsFull context

WorkflowsFull context

Any AI agent or app

WEXAYour enterprise
context

ConnectNormalizeGovernRaw dataGoverned context

Wexa SDK and MCPAny agent plugs in

From scattered enterprise data to a governed context graph

Connect, normalize and govern once. Every AI agent gets accurate context, fewer tokens and governed rules.

Scattered enterprise data

Databases

Data warehouses Snowflake

Internal systems SharePoint

WEXA

Governed context

Connect

Normalize

Govern

Ready for every agent

Accurate context

Optimized token use

Sovereign

How it works

Wexa functions in three layers

Layer 1Data normalization

Own your business context

CRM, ERP, ITSM, databases, mail, documents and chat connect into one context graph. It stays in sync in real time, and your company owns it.

Your business context graph

Salesforce

Snowflake

Outlook

SharePoint

Slack

Any data source

Connectors and ontology discovery

finds how the data relates

Customer

Invoice

Ticket

Policy

Owner

Payment

Layer 2Process normalization

Define and measure the outcome

Wexa mines how a process really runs from chat, mail, tickets, logs, transcripts and SOPs. Then it derives the to-be version, where agents run most steps and people approve.

Mined from

Slack

Outlook

Jira

System logs

Transcripts

SharePoint

Any source

As-isDiscovered

Request

Check

Wait

Manual re-check

Approve

Done

11 steps, 3 rework loops, 4 owners

To-beDerived

Request

ValidateAgent

EnrichAgent

ApproveHuman

ExecuteAgent

Sealed

6 steps, 0 loops, 3 run by agents

Layer 3AI implementation

Ship governed agentic outcomes in minutes

Your teams describe the workflow in plain English, in the coding tool they already use. The coding agent builds it on Wexa, and every agent inherits your context and rules.

Describe the workflowIn plain English, in your usual coding tool.
Coding agent reads the SDKFinds your context graph, actions and policies.
Agent generatedGovernance inherited, not written.
Governed run with evidenceAudited from the very first call.

Connects with your existing systems

Snowflake
SharePoint
Jira
Microsoft Teams
Excel
SQL Server
Outlook

The key differentiator

Our own graph DB makes connected agent queries fast and cheap

Wexa's own graph database connects enterprise data, enabling agents to query relationships in milliseconds and retrieve only relevant facts, reducing AI costs.

Tokens per query

98.7% fewer tokens per query

About 75 times lower token cost for the same queries

Tokens per queryRelative cost

Typical setup

202,285

75x

Wexa

2,668

Same queries on the same data. A typical setup sends the model whole documents; Wexa sends only the connected records each query needs.

Peak saving shown. On a typical day the saving is 85%.

Speed and size, same machine, same data

Wexa against the most widely used graph DB

Loading data relationships per second, higher is better
3.7xfaster
Wexa
118K
Other
32K
Reading records reads per second, higher is better
3.5xmore
Wexa
64.7K
Other
18.4K
Finding connected data median, two hops out, lower is better
4.9xfaster
Wexa
0.41 ms
Other
2.04 ms
Storing data per relationship, lower is better
4.7xsmaller
Wexa
106 B
Other
494 B

Tested on a public social graph of 3 million relationships, one 8-vCPU cloud machine, 40 clients at once, median of 3 runs. Four tests: load relationships, read records, find connected records two hops out, bytes stored per relationship. Token figures from our own retrieval benchmark.

Outcomes

Customers are already seeing results

Same process, measured before and after Wexa.

Supply chain
Connected
- Requests
- Contracts
- Vendors
What changed
Purchase orders are checked, completed and routed automatically.
0%
less time per purchase order
Before
7 days
After
2.5 days
85% fewer AI tokens per check
IT services
Connected
- Tickets
- Runbooks
- CMDB
What changed
AI agents resolve tickets using runbooks and asset records together.
0%
faster ticket resolution
Before
8 hours
After
4 hours
A third of tickets resolved automatically
Recruitment
Connected
- ATS
- Profiles
- Interviews
What changed
Hiring is automated end to end, from application to interview.
0%
shorter hiring cycle
Before
44 days
After
24 days
85% fewer AI tokens per screen
Mining
Connected
- Maintenance
- Fleet
- Safety
What changed
Maintenance processes are standardised, then automated with AI.
0%
shorter work-order cycle
Before
10 days
After
6 days
80% fewer AI tokens per step

Approximate figures calculated from customer workflows, before and after on the same process. Final measurements in progress.

Runs everywhere

Wexa runs on any cloud or on your own servers

Our cloud, your own cloud account, your data centre, or fully offline. Same context, same rules, same audit trail.

Your models

Any provider and any model

Route each task to the model that fits the job, from the major providers to your own custom LLM and ML models.

GPT, Claude, Gemini, Mistral, Groq, Azure OpenAI, Bedrock, Vertex AI

Hosted, private or local
Swap models any time
One context for every agent

Your infrastructure

Any cloud to air-gapped

The same context, rules and audit trail run wherever your security team says they must.

AWS

Google Cloud

Microsoft Azure

Your servers or air-gapped

Your keys, your boundary
Data stays where you put it
One install, any environment

Your tools

Build where your teams work

Agents are built over SDK and MCP, from the coding tools and agent platforms your teams already use.

Claude Code, Cursor, Copilot, Windsurf, Agentforce, ServiceNow, UiPath

Build in your coding tools
Plug in your agent platforms
Your own, over MCP and A2A

Governance

One set of rules everywhere

Policies, approvals and the audit trail travel with the context, whatever model, cloud or tool runs it.

You own the business contextSecuredGovernedAuditableCompliant

Rules written once, used by all
Every step in the audit trail
Approvals on high-risk actions

Security

Your data stays yoursEvery agent action is governed

Wexa runs within your infrastructure, using your encryption keys. Every agent action is checked and logged for audit.

AI agents

Claude
ChatGPT
Copilot
Your own agents

Your boundary

Policy

Who is asking, under which rules

Role and rules confirmed

Controls

01AI Constitution and AI Policy
06Roles, Departments and Projects

Access

What it may see and do

Sensitive fields masked, risky actions need approval

Controls

03Agent Clearance and Context Policies
02Enforcement and Guardrails

Audit

Every step recorded

Tamper-proof record kept

Controls

04Audit and Lineage, tamper-proof
05Compliance and AI Usage Controls

Your data

AI agents

Claude
ChatGPT
Copilot
Your own agents

Your boundary

Policy

Who is asking, under which rules

Role and rules confirmed

Controls

01AI Constitution and AI Policy
06Roles, Departments and Projects

Access

What it may see and do

Sensitive fields masked, risky actions need approval

Controls

03Agent Clearance and Context Policies
02Enforcement and Guardrails

Audit

Every step recorded

Tamper-proof record kept

Controls

04Audit and Lineage, tamper-proof
05Compliance and AI Usage Controls

Your data

The governed context returns the same way

Secure by designSovereign by default

SOC 2 Type I certified
GDPR compliant
ISO 27001
In progress
HIPAA
In progress

Your first pilot

Your first governed pilotlive within 72 hours

Start your enterprise AI transformation with one use case. Wexa connects your data and processes into governed context your teams can build on and scale.

Pilot path

72 hours

1
Connect
Connect your systems and build the context graph.
2
Map
Map one process, design the better version, estimate the cost.
3
Ship
Ship the first governed agent in the tools your teams use.
4
Scale
Add use cases on the same context, rules and audit trail.

Included

38 modules, one install. SDK and MCP for every app and agent. One backend, one bill.

Book a demo

Runs in your cloud, your VPC, on your servers or air-gapped. Response within one business day.