Reasoning assistants
Analysis tools for maths-heavy or logic-heavy questions, where the model's reasoning trace is reviewed or hidden depending on the audience.
AI platforms
DeepSeek development.
DeepSeek publishes open-weight models, including reasoning-focused ones that produce step-by-step thinking before answering. We use them where multi-step reasoning matters and where you want to host the model yourself.
A short call. Your first build, a fixed quote, and the timeline. No obligation.
What we build with DeepSeek
Where it fits.
Self-hosted code helpers
Code explanation and refactoring assistants running inside your network on a coder variant.
Distilled worker models
Smaller distilled checkpoints that handle high-volume classification and extraction on limited GPUs.
Private research summarisers
Pipelines that read internal reports and produce structured briefings without sending anything to an outside API.
When it is the right choice
Choose DeepSeek when
- →The task rewards explicit multi-step reasoning.
- →You want to run the model on your own hardware.
- →You are comparing open models and want a reasoning-focused option in the mix.
Worth knowing
Honest trade-offs.
- →Reasoning models spend extra tokens thinking, which raises latency and compute, so they suit hard tasks rather than simple ones.
- →Organisations with sourcing rules may restrict certain model families, which is worth checking before we build.
Often paired with
vLLMPyTorchHugging FaceDockerKubernetesPython
Related services
Services that use it.
Proof
Work built by the same team.
Closeum
13+ connected modules from calls through commissions
13+connected modules
5role types
32completed transactions
40+leads managed
SIIMS
Orders, production, warehouse, and dispatch on the same records
4operational roles
37backend tests passed
17hosted workflow tests passed
Ledgerline
603 tests passed in a dated financial-control verification
SAR 760Kcash reconciled end to end
603tests passed
14control findings fixed
3finance sources in one ledger
Common questions
Before you start.
Should we show the reasoning to users?
Usually not by default. We keep the trace for debugging and audit, and show users the final answer with sources.
Can we use the hosted API instead?
Yes, for prototypes. Teams with confidentiality needs should host the weights themselves, which is the main reason to pick an open model.
Are distilled versions good enough?
For narrow tasks they often are. We test the distilled and full versions on your data and pick the smallest one that meets the bar.
What do you build with DeepSeek?
Reasoning tasks, Self-hosted deployment, Cost-efficient inference, Fine tuning, and related work. We choose DeepSeek when it is the right fit for the product, the team and the budget.
Can you work with our existing DeepSeek code?
Yes. We can review what you have, fix what is fragile, and extend it, or build alongside your team.
Keep exploring
More than DeepSeek.
Where we apply it
The Audit
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