Copilots & assistants
In-app assistants that understand your product and your user.
Language models, built into your product.
We turn language models into dependable product features: copilots inside your software, generators for content, and tools that summarise, classify and extract at scale.
Planning
Goal
Output
Working…
- Validated output
- Your data stays yours
- Cost tracked per request
How we build LLM features
From prompt to production feature.
- 01
Define
We agree what good output looks like, using real examples.
- 02
Design
Prompts, tools and output formats are built around your data.
- 03
Choose
We pick the model that fits the quality, speed and cost you need.
- 04
Guard
Validation, retries and fallbacks catch bad or off-format output.
- 05
Measure
Evals and usage tracking keep quality and spend in check.
What we build
Model features that hold up in production
Prompt & model engineering
Structured prompts, function calling and model selection for cost and quality.
Fine-tuning
Models tuned on your data for tone, format or domain accuracy.
Extraction & classification
Turn emails, forms and documents into clean, structured data.
Model integration
OpenAI, Anthropic, open-source and self-hosted models behind one API.
Cost & latency tuning
Caching, routing and streaming keep responses fast and affordable.
Use cases
Where teams use it first
SaaSIn-product copilot
Users ask for reports, drafts or settings changes in plain language.
Your app→Copilot→Actions
MarketingContent engine
On-brand product descriptions, emails and posts generated and reviewed in one flow.
Catalogue→Brand voice→CMS
RecruitmentCandidate screening
CVs and interviews summarised into structured, comparable scorecards.
CVs→LLM→ScorecardsCustom vs. off-the-shelf
Why not just use a chat tool?
| Capability | Manual work | Generic chat tool | Custom LLM feature |
|---|---|---|---|
| Works inside your product | No | No | Yes |
| Uses your data and rules | Yes | Partly | Yes |
| Consistent output format | Varies | No | Yes, validated |
| Handles thousands of items | No | Copy and paste | Yes, in batches |
| Quality and cost tracked | No | No | Yes |
LLM products we've shipped
Running in production today
Content engineSuperContent.ai
An AI content platform that writes blog posts and website copy in 25+ languages across 50+ content types.
Multi-LLM
Yashraa
A chatbot, voice agent and Chat LLM workspace that compares answers from leading models side by side.
AI SaaS
SignSuiteIQ
AI mockups, proposals and plan reading for sign and graphics professionals.
Process
From first call to production
01
Scope
A short workshop to pick the use case, define what success looks like and check your data.
02
Prototype
A working demo on your real data within weeks, so you can see it before you commit.
03
Build & integrate
A production build connected to your tools, with guardrails, tests and monitoring.
04
Launch & improve
We go live, track quality and cost, and keep tuning as usage grows.
Built withOpenAIAnthropicLlamaNext.jsNodePython
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