KovaServeKovaServe
For coding + terminal agents

Build coding agents your users actually trust.

Call the Agentic Inference Cloud. Every model call becomes a durable, resumable, cache-aware, budget-safe run, so a 40-minute task survives a laptop close, a process crash, or a runaway loop.

Your users' biggest complaint isn't quality. It's that the agent crashed at step 47 and lost 25 minutes. That your API bill is unpredictable. That there's no way to pause.

Apply to the design partner program Try the playground
Crash + resume
Same GPU. Same context. 4.2 seconds.
Preview of Q3 capability
run_01HK4Q · coding-agent-v3idle
step 0 / 52
Budget meter
Cap: $5.00 / run
Preview of Q3 capability
70% · WARN
90% · DEGRADED
0–70%
Normal operation. Run continues at full speed.
70–90%
Warning chip surfaces. Operator is notified. Run continues.
90–100%
Degraded mode. Non-critical tool calls are throttled.
100%
Hard stop. Next inference call returns 429. Saved: $500.
What your product gains

Primitives you'd otherwise build for a quarter.

Resume at step 47, not step 1

Every run checkpoints automatically. A crash or disconnect resumes on the same GPU with the same context, in under 5 seconds.

Hard budget caps

Runaway loops can't bill your users $500. Set a cap per run in dollars, tokens, steps, or time. The next inference call returns 429.

Warm-route routing

Every step of a session lands on the GPU that already holds its KV cache. 30–70% lower cost on repeated-state work, measured from real cache counters.

One replay per support ticket

"What did the agent do?" stops being a log-grep. One API call returns the full, replayable run with tokens, costs, tools, and GPU affinity.

Bring your own runtime, or use ours

LangGraph, Temporal, a custom loop, or the KovaServe runtime for coding/terminal agents. Same API either way. One URL change, zero agent rewrite.

Before / after

What changes for coding & terminal agents.

Without KovaServe

  • Agent crashes → user loses 25 minutes
  • "What did the agent do?" → grep CloudWatch
  • Runaway loop → $500 surprise on the bill
  • Every step hits a cold GPU
  • Cost per task = your best guess
  • "Pause this" = wishful thinking

With KovaServe

  • Agent crashes → resume in under 5 seconds
  • "What did the agent do?" → one API call
  • Runaway loop → hard-stopped at your cap
  • Every step lands on the warm GPU
  • Cost per task = a measured number
  • "Pause this" = actually pauses
How you adopt it

Three levels. Pick one and ship.

1
Change one URL
15 min, zero agent rewrite

Point your OpenAI-compatible client at api.kovaserve.ai/v1. You immediately get cache-aware routing and real cost metering.

2
Add one line
1 hour, full observability + budgets

Wrap each task in client.runs.create({run_id, budget}). Every step is now tracked, every run is replayable, every budget is enforced.

3
Go all the way
1 sprint, the whole platform

Wire checkpoint hooks in your agent loop. Fork runs. Branch alternatives. Pause and resume on user action, not crash.

Run timeline
run_01HK4Q · 20 steps
1
step 1 · model_call · qwen3-4b · 60ms · $0.0080
cache MISS
2
step 2 · model_call · qwen3-4b · 69ms · $0.0100
cache MISS
3
step 3 · model_call · qwen3-4b · 78ms · $0.0120
cache MISS
4
step 4 · model_call · qwen3-4b · 87ms · $0.0080
cache HIT
5
step 5 · model_call · qwen3-4b · 96ms · $0.0100
cache HIT
6
step 6 · model_call · qwen3-4b · 60ms · $0.0120
cache HIT
7
step 7 · model_call · qwen3-4b · 69ms · $0.0080
cache MISS
8
step 8 · model_call · qwen3-4b · 78ms · $0.0100
cache HIT
9
step 9 · model_call · qwen3-4b · 87ms · $0.0120
cache HIT
10
step 10 · model_call · qwen3-4b · 96ms · $0.0080
cache HIT
11
step 11 · tool_call · qwen3-4b · 60ms · $0.0100
cache HIT
12
step 12 · model_call · qwen3-4b · 69ms · $0.0120
cache HIT
13
step 13 · model_call · qwen3-4b · 78ms · $0.0080
cache MISS
14
step 14 · model_call · qwen3-4b · 87ms · $0.0100
cache HIT
15
step 15 · model_call · qwen3-4b · 96ms · $0.0120
cache HIT
16
step 16 · model_call · qwen3-4b · 60ms · $0.0080
cache HIT
17
step 17 · model_call · qwen3-4b · 69ms · $0.0100
cache HIT
18
step 18 · model_call · qwen3-4b · 78ms · $0.0120
cache HIT
19
step 19 · model_call · qwen3-4b · 87ms · $0.0080
cache MISS
20
step 20 · model_call · qwen3-4b · 96ms · $0.0100
cache HIT
Total cost
$0.42
Cache saved
$0.23
Duration
4.2s
Proof

Numbers that matter for this workload.

Resume at step 47, not step 1.

Tasks that survive a crash.

Hard budget caps, enforced at the inference boundary.

30–70% lower inference cost on repeated-state work.

Pricing highlight

Startup tier is usage-based with unmetered runs and a cache discount. Design partner program has 5 slots open.

See full pricing
How you start

Three steps. Most teams ship within the hour.

1

Sign up

Create a free account. Credit card, no sales call.

2

Change your base URL

One-line swap in any OpenAI-compatible client. You're now calling the Agentic Inference Cloud.

python
base_url = "https://api.kovaserve.ai/v1"
3

Ship

Every call is now a durable run. Inference, runtime, state, and recovery, bundled. Cache savings and cost attribution come automatically.

Start freeRead the docs

Stop assembling inference, runtime, state, and recovery yourself.

Call the Agentic Inference Cloud instead.

Design partner program open. 5 slots this quarter.

Start free. No credit card, no call.Talk to a founder