Capabilities

Scopedbeforeyousign anything.

AI automation consulting, custom LLM and RAG implementation, AI agents and legacy modernization. Every capability below states what it includes, exactly what lands in your hands, and how long it takes. No “it depends” until we've actually looked at your systems.

9Capabilities
4Ways in
1–3 wksFastest engagement
FixedDeliverables per scope

The cheapest thing that works
wins.

Four system classes, honestly compared. Most engagements start with the simplest one that solves the problem and earn their way up — we'll tell you when you don't need the expensive option.

I need AI to…
Start with

RAG Knowledge Base

Retrieval over your private documents with cited, permission-aware answers — the model sees only what the asker may.

First working version
2–3 weeks
Best for
Policy/document Q&A, research, onboarding, compliance lookup
What it needs from you
Existing documents — messy is fine, missing is not

The questions you were
going to ask anyway.

It ranges honestly. A RAG assistant over existing documents can be live in 2–3 weeks. An autonomous agent with deep system integrations typically takes 3–8 weeks to supervised production. Legacy modernization is phased — first extracted capability in 4–8 weeks, the full roadmap over months. We scope precisely during discovery and show working demos throughout, so you're never guessing at progress.

For individual productivity, you should — it's excellent. The gap appears at the system level: ChatGPT doesn't know your data, can't act inside your CRM or ERP, has no audit trail, and offers no guarantees about where your customers' data goes. We build AI that's grounded in your private data, wired into your workflows, and governed to your compliance requirements. Different tool, different job.

Less than you fear, more than zero. RAG systems work with the documents you already have — messy is fine, missing is not. Custom predictive models need historical data, and we assess whether yours is sufficient during the audit before you commit to model work. If your data isn't ready, we tell you that and fix the pipeline first — training on bad data just automates your existing errors.

Yes — that's half our practice. We connect through APIs where they exist and build facades where they don't, including mainframe and on-prem systems. The strangler-fig approach means your legacy core keeps running untouched while new capabilities wrap around it. Zero-downtime is an engineering requirement we design for, not a marketing phrase.

Architecture-first, not policy-after. Options include private model endpoints, on-premise or VPC deployment, PII redaction before any model call, and audit logs for every AI action. For regulated industries we map controls to HIPAA, SOC 2, or GDPR during design — and our security practice red-teams AI features for prompt injection and data leakage before launch.

With a free 45–60 minute diagnosis call. If the problem is big enough to need a closer look, a paid two-week discovery sprint follows, and its fee is credited against the build if you hire us. In the sprint we map your workflows and data, rank the opportunities by value and feasibility, and produce a concrete proposal with architecture, timeline, and cost. You own everything it produces. If the honest answer is that AI isn't your bottleneck, the discovery report says so.

AI systems degrade without care — models drift, prompts rot, costs creep. Every build ships with monitoring, an operations runbook, and a handover so your team can run it. Beyond that, we offer ongoing optimization retainers, but they're optional: we build for your independence, not our lock-in.

Claude, GPT, Gemini, and open-weight models like Llama and Mistral — selected per use case on accuracy, latency, cost, and data-privacy requirements, tested against your actual tasks. We're vendor-neutral by design, and every build includes a model-swap procedure so you're never locked to one provider's pricing or roadmap.

One free call.
Then only what earns its place.

  1. 01

    Diagnosis call

    Free · 45–60 minutes

    You tell us what is slow. We tell you where we would look first, written down and sent to you. What we write is yours to keep.

  2. 02

    Two-week audit

    Paid · credited against the build

    For bigger problems: an audit of your systems, data and workflows, ending in a ranked list of where AI earns its keep, and where it does not.

  3. 03

    Build & ship

    2–12 weeks, by service

    Built and shipped into production behind a feature flag, tested, with rollback ready, and integrated without stopping operations.

  4. 04

    Run & improve

    Ongoing

    Monitoring and fixing after launch, because AI quietly gets less accurate if nobody watches it. Then the next win.

Not sure which one you need?

That's normal, and it's the first thing we work out together. Bring the problem, not the solution.