OUR
SERVICES
Our services are most simply described as:
- Conducting research & collecting intelligence
- Developing software - prototyping & MLOps
AI RESEARCH & INTELLIGENCE
RESEARCH
WHAT DO YOU NEED TO KNOW?
BY WHEN?
You don't need to know all the nerdy, bewildering details and nuances of deep neural networks - leave that to us, so you can focus on your business.
We believe in explaining things in the simplest possible terms to help people get stuff done. We don't hide behind acronyms to look clever - and we don't write long reports nobody will ever read.
A research project with Osinto:
- Answers an agreed set of questions
- Is delivered via a briefing session with Q&A
- Has a defined end date and cost agreed before kick-off
INTELLIGENCE
WHAT DO YOU NEED TO KNOW?
HOW OFTEN? AND FOR HOW LONG?
Osinto's intelligence briefings are simply ongoing research projects - where we report back answers to an agreed set of questions more than once.
Findings are shared at a defined frequency - daily / weekly / monthly - and in the format most useful to you eg. email, pdf, , audio, video, virtual / in-person briefings, on WhatsApp or even via a good old fashioned telephone call!
Osinto's intelligence services:
- Answer an agreed set of questions, at an agreed frequency
- Are delivered in the format most usable by you
- Have a defined end date and cost agreed before kick-off
AI STRATEGY
WHAT ARE YOU TRYING TO ACHIEVE? WHY?
HOW COULD YOU DO IT? WHY LIKE THIS?
At some point you need to take what you've learned about AI and decide upon the actions you're going to take. We're always biased towards action and hope customers will work on some sort of AI prototype (see below).
For others some further justification, structure and process is required. If you're going to build an in-house AI competence for example, engage an external service provider, or justify increased spend on third party cloud / on-premise storage and compute.
Osinto can work with you to develop an AI Strategy - helping companies who aren't AI experts to make decisions and set a course of action:
- Typically a 1-2 page strategy document
- Outlining what you're trying to achieve with AI, and why
- Setting out a process to evaluate and iterate
SPECIAL PROJECTS
SOMETHING BESPOKE?
DISCRETE SERVICES FOR PRIVATE CLIENTS.
If you've got something else AI / ML related that you'd like to work with us on, then please don't hesitate to get in touch. We've scouted for investment funds, corporate accelerators, and family offices, mapped and tracked markets for governments and other institutions.
We are particularly interested in projects related to computer vision, small language models, multi-modal / embodied AI and robotics, AI compute, data centres, cooling and on-device / edge AI deployments and use cases.
We're happy to share our collective skills, network and experience in AI / ML in exchange for a fair fee:
- Outline your requirement
- We'll respond with a proposal and price
- Timelines and cost are always agreed before kick-off
AI PROTOTYPING & MLOPS
AI PROTOTYPING
HOW DO WE GET STARTED?
WHAT SHOULD WE BUILD?
The best way to learn is by doing - and that's why we love spinning up prototype products. Some call them 'Minimal Viable Products' (MVPs), others proofs-of-concept.
Semantics aside - we love building these first, dirty, hacked together versions of software-derived products / services. Between us we've been doing it for decades.
And because we always have an eye on the next set of headaches, we'll help you and your team develop prototypes with an architecture that's designed to scale, from day one.
A prototyping project with Osinto:
- Should be quick to execute and test a specific hypothesis
- Benefits from our MLOps expertise and best practice
- Is defined up-front; with clear goals, timelines and costs
MLOPS
WHAT INFRASTRUCTURE DO WE NEED?
CAN'T OUR DATA SCIENTISTS HANDLE THIS?
Believe us when we say there's an ocean of pain between spinning up a novel AI prototype and deploying production ready software services!
And to answer our own question above - no, the scalable infrastructure that underpins production ML is not the domain of the Data Scientists who might build models.
Navigating the world of Kubernetes containers, elastic compute clouds and Infrastructure-as-a-Service (SaaS) are your MLOps team, if you have one...
If not, use ours - and hit the ground running:
- Have your stack architected by seasoned MLOps pros
- Learn from all the mistakes we've already made
- Build scalable systems that use infrastructure efficiently