Most common
A private AI workspace.
Give your whole company secure access to AI — without giving up your data. Self-hosted, multi-model, rolled out team by team.
- Self-hosted
- Any model, switchable
- Wired to your identity & systems
- Adoption that sticks
Services
Four shapes of engagement.
Most engagements start as one of these. Tell us where you want to begin — we'll shape the scope and timeline around your team.
AI woven into your operations.
Custom agents that live where your team already works — drafting, triaging, summarising. The unglamorous work AI is actually good at.
- Editorial & content workflows
- Comms, briefs and drafts
- Document and inbox triage
- Multi-language support
AI inside your product.
Ship AI features in the product you sell — search, vision, summarisation, generation. Built to scale, owned by your team.
- Search & retrieval at scale
- Vision & metadata pipelines
- Generative product features
- Evals, observability, cost control
Strategy & enablement.
Workshops, audits and short prototype sprints for leadership teams figuring out where AI actually moves the numbers.
- Opportunity mapping
- Roadmap & ROI modelling
- Model & vendor selection
- Hands-on team enablement
The workspace
Buying a seat for everyone is the wrong shape of solution.
Our most common engagement is a private AI workspace — built on LibreChat, deployed inside your environment, rolled out across the org. Here's why it usually beats a per-seat SaaS.
Every model, one workspace
Anthropic, OpenAI, Google, Meta, Mistral, your own fine-tunes — your team picks the right model for the job, switches mid-conversation, and you control the bill.
Your data stays yours
Self-hosted in your cloud, on your infrastructure, behind your firewall. No prompts, no documents, nothing leaves your tenant.
Custom agents per team
We build assistants tuned to your workflows — a draft-helper for your editors, a brief-writer for marketing, a triage agent for ops.
Connected to your tools
Plug it into SharePoint, Google Drive, Slack, Confluence, your CRM, your data warehouse. Answers cite your sources.
Enterprise-ready by default
SSO, role-based access, content filters, prompt-injection guards, full audit trails. Built for compliance teams to sign off, not work around.
Usage you can see
Per-team and per-user dashboards. Cost per department, model mix, where AI is actually moving the needle. No black box.
Buying ChatGPT Enterprise
Closed, per-seat, single-vendor.
- $30–60 per employee, per month — rising
- One model. One vendor. No portability.
- Your prompts and uploads sit in their tenant
- Limited integration with your internal tools
- Hard to govern; harder to measure ROI
Your private AI workspace
Open, multi-model, yours.
- Pay per token, not per seat — typically 60–80% less at scale
- Any model. Switch when better ones ship.
- Self-hosted; data never leaves your tenant
- Wired into the tools your team already lives in
- Visible usage, visible cost, governable on your terms
What we build into it
A workspace your whole team will actually use.
LibreChat is the foundation. The work is the integrations, agents, governance and operations on top — what turns an installation into a platform people open every day.
Book a 30-minute walkthrough01
Hosting & architecture
Stood up in your cloud or on-prem, right-sized for your headcount and your security posture.
02
Models & routing
Plugged into whichever providers your policy allows. Smart routing keeps the right model on the right job and the bill predictable.
03
Identity, access, audit
SSO via your identity provider, role-based access, group-level policies, full audit logs. Your compliance team signs off before pilot.
04
Your data, in context
Connected to wherever your knowledge actually lives — drives, wikis, ticket systems, your warehouse. Answers cite their sources.
05
Agents per team
Assistants shaped to how each team actually works — editorial doesn't need what finance needs, finance doesn't need what ops needs.
06
Adoption & operations
Training, internal champions, monthly model reviews, ongoing agent tuning. We run it like a product.
How we work
Land it well. Then grow it across the org.
Whether it's a workspace, an agent or a feature in your product — most AI projects fail in adoption, not architecture. We treat rollout as the work: pilot tightly, train properly, scale only as fast as the business is ready for.
01
Land
Weeks 1–3
We get the platform running, in your environment, with your identity.
- Architecture, hosting decisions, model routing
- SSO and access controls wired to your IdP
- Initial agents and prompts seeded for your business
1 environment
production-ready
02
Pilot
Weeks 3–6
One team, real work. We learn what AI actually changes for them.
- Pick a team with sharp problems and willing leadership
- Build the agents and integrations that move their week
- Measure adoption, time saved, quality lift
1 team
working in it daily
03
Roll out
Months 2–4
Department by department, with training that sticks.
- Use-case workshops by function (ops, marketing, finance, support)
- Hands-on training, internal champions, office hours
- Workspace-level governance, content filters, role-based access
5–15 teams
across the business
04
Operate
Ongoing
We keep it sharp. New models, new agents, new integrations.
- Monthly model and stack reviews — adopt the better thing fast
- Usage analytics, cost optimisation, agent tuning
- Hand-off when you're ready, retainer when you're not
Whole org
using it as a habit
Next step
Ready to talk about your engagement?
Most engagements start with a 30-minute call. We'll talk about what your team actually needs, walk you through one of our deployments, and tell you honestly whether we're the right shop for the job.