Zyvra Studio · Birmingham, UK
Security-first software, shipped fast.
Most enterprise software is either properly architected or shipped fast, rarely both. I do both, using AI as the build accelerator. Real production architecture, secure by design, deployed where you choose (any cloud, on-premises, or hybrid), with code your team owns from handover.
15 years across IT, cyber security, architecture, databases, business analysis, and QA. I've seen what makes complex enterprise deployments fail at the security gate, in production, and in audit. The studio is built from that experience.
If you're earlier than that, start the conversation anyway. We'll tell you honestly whether this is a fit, and if not, point you somewhere that is.
One engagement, one fixed price. No phases to climb, no separate invoices to approve.
We scope it, build it, and ship it to your environment, then hand over the code, the infrastructure-as-code, and the runbook. Your team owns it from day one. One fixed price, agreed on a free scoping call.
Teams with a build stalled at security, integration, or cost, who want it live and owned without a long enterprise engagement.
A free scoping call, then a short assessment: security boundaries, data residency, integration paths, and a 3-month cost model. We confirm your tier and quote one fixed price. An honest go / no / conditional answer before you commit.
The production architecture, built in your own environment and integrated with your real systems, behind your auth, with logging and cost guards from the first request. An early feasibility checkpoint in week one means either side can stop cleanly if something doesn't hold up.
Live in your tenant with monitoring and alerting routed to your on-call. Full handover of code, IaC, and runbooks, yours from day one, plus 60 days of post-launch support. Zyvra has zero ongoing access after that.
One fixed price per build: £2,000, £5,000, or £10,000 by tier. Introductory launch rates, locked in for your engagement, rising after 30 September 2026. See the full pricing breakdown →
If your build uses AI, the bill is rarely a surprise on day one. It surprises you six months in, when call volume grows, workloads drift toward a more capable model, or a cheaper model launches and nobody re-evaluates. The fix is lifecycle discipline, not a one-off cost estimate.
Models matched to the workload, not a default. Claude Haiku for routine extraction and classification, Sonnet for reasoning-heavy tasks, Opus for complex analysis. Embeddings (Voyage AI or similar) sized to the vocabulary you actually have. Costed at projected volume in the 3-month cost model scoping produces.
Every request metered from the first day of the build. Actuals reported weekly against the scoping projection. If reality diverges from the model, you find out in week 2, not month 6. Per-user, per-tenant, and per-day caps are wired in so a single request cannot escape the budget.
Where most AI builds drift. The bit other shops do not talk about. Cost gets watched automatically by the system and manually on a calendar, with the cadence written into the runbook your team owns.
Production AWS infrastructure for the moment a regulator turns up in eighteen months and asks for the audit trail of every AI decision a system made. Three open-source repos that work together.
audit-ledger is the AWS stack. DynamoDB for live query, S3 Object Lock in COMPLIANCE mode for the immutable copy, 7-year retention by default. PII is hashed at the client so personal data never reaches the ledger. Designed with EU AI Act Article 12 and FCA SS1/23 sitting open on the desk.
audit-ledger-mcp is the Model Context Protocol server. Published to npm. Listed in Anthropic's official MCP Registry alongside the reference implementations from Anthropic and GitHub. Drop one config block into Claude Desktop, Cursor, or a LangGraph adapter and the agent can write to a tamper-evident audit trail. Zero-config public sandbox built in.
langgraph-loan-triage is a working demonstration of the full pattern. Triage agent, then risk agent, then a human-in-the-loop step. Each step records an audit event.
Article 12 sets a six-month floor on retention. Layer FCA model risk on top and you're looking at six to seven years. This is the architecture for that question. The compliance posture is the part you can't bolt on later, and that part is built.
Available as a product from £10,000. Hosted and managed by us, deployed into your own AWS account, or handed over as code. Or self-host the open source for free.
Repos: audit-ledger · audit-ledger-mcp · langgraph-loan-triage. Try the MCP server with zero config: npx -y audit-ledger-mcp.
Job searching is slow, and generic advice rarely helps. Most people know their CV needs work but can't see what to change, and most tools give the same tips regardless of role.
We built CareerIntel AI for serious job seekers who want real support across the full journey: CV tailoring, cover letters, interview preparation, and salary negotiation, with application tracking and pattern analysis built in.
The subscription product is live and accepting users. A CV revision session takes under 5 minutes instead of the usual hours of self-editing, and the output is personalised for the role, industry, and seniority.
Visitors wanted quick answers about services without reading every page. Static FAQs go stale, and a generic LLM makes things up. The right answer was a retrieval-augmented chatbot grounded in actual content, with source citations on every answer.
A Node.js API, Voyage AI embeddings over the site's content, and Claude as the reasoning layer. The index updates automatically whenever content changes, so every answer comes from real site content. Nothing invented.
Try it: "What does a build engagement include?" or "How does Zyvra handle data under the EU AI Act?"
We'll give you an honest assessment of whether this is a fit and what the right next step would be. You'll get a reply within two business days from Shahid, the engineer who'll build it.
Or email directly: hello@zyvra.studio